 Good morning. Good morning, everybody. Welcome. I'm very happy that you are here. And I just want to start with one important thing. The most important thing is let's discuss openly, okay? Because blockchain is a hot topic. It's a controversial topic. People talk about it. There's a lot of hype involved. And let's talk like really open. If we don't do it here, nobody else will do it, okay? So that's a good thing. And well, we are doing live streaming. So I have to announce it. And I don't ask you for like to fill out some papers. We don't do this stuff, right? But so if somebody of you doesn't want to be on the camera on the live stream, we can like work something out that the camera will never go to this corner, because the camera will actually record even the people in the audience who ask the question, yeah? Who ask the question, so. But one thing, we are not here to record a perfect live stream. The Cyber Academy team is doing a very great job, I can already tell. And I'm very thankful for that. But if you need to, yeah, I give them a round of applause. But if you feel the urge to just shout without waiting for the microphone, just do it, okay? And do it loudly enough, okay? Good. This was this thing. And well, the Wi-Fi, I wrote a lot of emails. And I tried to make it as open and as fast and as free as possible. But this is like where we ended up in a complex sign up process. And it's fast enough to write emails. Okay, I hope it will like work out. Okay, so the live stream will be under creative comments. And if you hear something that you want to like that is new to you or that you learned during the live stream, I ask you to reference it or reference the content that this person who's talking about it has published under maybe a blog post or somewhere else, okay? So it should be referenced, okay? And this is like for all publishers, right? Who hear this, yeah? And so the speakers, we will not share the presentations in a centralized way. But I ask the speakers to upload their presentations if they want to or share the presentations with the telegram group or upload them to slide share if they want to, okay? And well, we have our telegram group. And we can use the telegram group to share links and do organization, okay? So I'm pretty sure that you are all familiar with telegram. This is like the message of the blockchain community. We keep the intro short. So there will be only a few lines. If you think as a speaker that we missed something, you just added yourself, okay? It's completely okay here. And I think it's a better way than just like coming up with a lot of darts here in front of effort talk, okay? And well, I have one last thing that I have to announce. I've been often asked or we are often asked to do an ICO here, Blockchain for Science, yeah? So you know the token economy and I'm proud to announce the Blockchain for Science ICO today. It's the initial sticker offering. You'll find the stickers outside. So the stickers and on your badge, there's like a field like next to your name. And you are the only one who is allowed to put a sticker there. And like in the social media wall, you and the other person can put a emoticon there, okay? And you can write down what you want to be asked about on your badge, okay? So it's all about integration and communication. Get to know each other, right? And I'm almost done with my introduction and I'm happy to introduce Toshi to you. Toshi is the director of internet-based innovations at the Humboldt Institute of Internet and Society. And we are happy to like announce this conference under the auspices of this institute. Thank you very much and welcome again, yeah? Okay, look. Good morning. Yeah, so it's a pleasure to open this conference together with Zunke, of course, from the Alexander von Humboldt Institute. We support that initiative since the first ideas, I think. Yeah, so and so I'm very happy to be here. Let me give you some information about firstly me and then the Humboldt Institute. Of course, I'm responsible, as you mentioned, for internet innovation and innovation and society. So we do the research about the question, what does the internet does with this earth as individuals, as companies, as society? And so one main fact, of course, is to handle technology. New technology comes up, blockchain, and even in the area of blockchain for science, the idea came up. And so the idea of the Humboldt Institute is to focus on these kinds of questions and find out which are the main points where we could support these ideas. And so that was one of the first days when Zunke started a research group in our institute, and we had roundtables and talked about how could we use the blockchain technology even for science. And so the idea was to discuss this and I'm very happy that Zunke had their initiative to do this conference, of course, to bring people together and from all areas, from friendly other research institutes. And so from experts from the scene, that is also our impact to bring together different disciplines. So I'm one of the directors of that institute coming from computer science and other colleagues, director colleagues come from law, from societal research, from business administration research. So we try to bring together all these ideas and doing research on a broader base. And one of our first projects, I guess, was that open science book Zunke wrote with one of our colleagues, Sascha Frisike, is coming tomorrow, I heard. And so I'm very proud about that, even if I'm not the author, but you have 458,000 downloads on Springer. So that's number one. And one of the first ones who was open, it was kind of an open book download book. So if you never had that download currently, so just maybe you can close the 460,000 gap during these days. And yeah, now blockchain for science and this conference, the idea was to find out what blockchain can do for science and knowledge creation. And so to analyze the impact of science and knowledge creation, and even it could help us to find new ways maybe of funding research with blockchain technology or shared data. So to be sure that the one who own the data and the one who uses the data have the right track and history on that case. And so that might be one point which is going to be discussed in the conference or in one of the workshops, which will start. So our ideas and examples were to think about how to use blockchain technology for data, but also for links, identities of researchers and other cases which might come up. And so our focus is to have more safety on data we use for science and so that could be one perspective in that area. And of course we are thinking about new funding models in research using blockchain technology. And so at this time we did not only analyze and research the field, we tried to influence it. And this conference and Zwinker's vision is to build up a community which is influencing their blockchain for science idea. And so we would foster in that conference cooperation of course between people and institutes, prevent wallet gardens as you said it's an open talk conference and so we try to open up our minds. And this is an integral part of this effort, this conference which is starting today. And even Berlin, you have seen we are part of the Berlin Science Week and even Berlin is in a perfect situation and condition cause. We have a lot of successful initiatives here started in Berlin and so I'm happy that we have that conference that you decided to start the conference here. You could do that anywhere but you decided for Berlin and so I'm very happy and we have a lot of initiative, Bundesblock for example, coming up with maybe a new German blockchain law and so there are a lot of initiatives situated here and we have the chance to look how to enable this idea even blockchain for science idea. And so let's start with that conference and even blockchain might have been a kind of a hype with a very high peak during the last year. Maybe lots of you got a lot of bitcoins and so the crypto economy craziness how you call that that ended maybe beginning of this year after a downslope but now we are sure that we are in the hype curve now on the stable plateau about blockchain, blockchain for science and so we can have a fundamental claim of blockchain to drive that to a real successful story and just end with a kind of an outlook maybe you have seen and heard that this conference is followed by a lot of meetups, small conferences, workshops, hackathons even at my institute and also on code academy and other partners in Berlin so if you don't have it done yet just sign in and so I will finalize it with a great thank you to Zönke for the initiative on your vision to start this conference and I'm happy to be here and have a wonderful conference. Thank you Zönke. Thank you, thank you Toshi for the introduction and welcome and for your support and as you heard we are in the plateau of productivity in the hype curve right and it is a conference so we have to work and discuss and see what is in there or blockchain and science okay and now I'm I'm very happy to introduce the next speaker the first speaker it's Professor Diernagel from the department of experimental neurology of the Charité University hospital and he is known in the open science scene very well and I just hand over the microphone to you. Thank you very much so I hope you won't regret having me invite it especially as the first speaker because it'll be controversial and so if you fire this up my slides are on OSF as always so there's a there's an URL so my slides are there I should start with a disclaimer and the disclaimer is that I'm not going to talk about blockchain and science in general I think there are quite a lot of useful and interesting applications that are coming up what I will talk about is the context of the blockchain in terms of increasing value in I think the blockchain community does have a really big role to play here so there's a lot of great thinkers in this room a lot of great tech people a lot of great researchers a lot of great librarians as well and I think what you all need to do is coalesce together more as a sort of consortium or a community to begin to challenge the the other side of this so for example the STM association they call themselves the global voice of scholarly publishing they essentially do all the sort of politics and the lobbying on behalf of the the established scholarly publishing industry like why don't you want to take them on like build a consortium where you take them on in the name of open science so all of you people in this room come together and don't just make it blockchain for science make it blockchain for open science right how cool would that be and you know you actually come together and you share your ideas you collaborate because you have this common goal which you all want to address and you realize what you're fighting against and the steps that you need to to to take to overcome this and then you can collectively address together the issue of governance of public research and you know who owns access to public research this this is it and you know ultimately I'm going to steal a quote here from Brian Nosek and and Chris Chambers and say you know future generations but this is what we want right we'll look back on the term open science as a tautology a throwback from an era before science woke up and open science will simply be known just as good science or science and the close secretive practices that define our current culture will seem as primitive to them as alchemy is today and that's sort of what we want to achieve right so hopefully a lot of you recognize the logos here and let's build blockchain for open science as well so yeah thank you very much John thank you thank you very much for your talk okay so we'll have three questions okay John yeah okay good so am I a common question or we just continue with the next one John there was a fantastic talk and I couldn't agree with you more but the only question that I have for you is how do we work with the publishers instead of having them on the other side and telling that they do something wrong which is in a lot of ways they do harm but how do you bring them back to the table in order to achieve this logical how do you make them your allies instead of instead of having the other on them on the other side so that's a really good question so you know I don't think necessarily is always us versus them so in fact I think people from here are from digital science and they're working on this amazing blockchain-ified open peer review process I don't know if anyone's here yeah and that's a really great initiative with catalysis and Springer Nature, Wiley, TNF all joining in with us and that I think is really great but like ultimately you have to ask you know what do we all want and can the tension between you know this incredible for-profit motive of players like Elsevier, Springer and others be reconciled with that you know if you have CEOs taking home like 14 million dollars a year and you know three thousand bucks for an APC 40 percent of which just goes straight into shareholder pockets you know or five thousand two hundred in the case of like Nature Communications you know you have to ask can that be reconciled with what we want to achieve I don't have an answer for that I think it has to be assessed on like an individual basis based on the values of you and and your own companies and these are really difficult questions but it's not up to me to define that for you all I would just say think about how you reconcile the tensions and between what you want to achieve and the motivations of these big companies. Hashtag not all publishers. You asked a question regarding if yeah if anyone knows a kind of a secret scenario how to reach your goal well there are lots of literature about change management so this is typically a situation of having a bad habit in the whole system this is a systematic error and it's not really possible to solve this problem with only scientists and from small communities there is an institutional support which is really needed and you have to take along the academic institutions and of course the publishers with you and there are the major issue what I see now is that there are European Union funded projects which are really forcing this this is a kind of top-down effort and then there is a bottom-up effort which is coming from these kind of communities but in between there are these institutions which still have the good old habits not to convince not to go through but if you could tackle that one getting along institutions yeah using change management that would be I think the the possible scenario yeah I totally agree like if if we go back to like the penguin scenario I don't think we're in the phase where everyone's still sitting on the iceberg I think enough penguins have slid down the iceberg now that people are beginning to realize that this is the future like open science is the future open access policies are taking off all over the world at different levels and open science ones too and you know the future is definitively open but we have to be in a position where we're defining that trajectory right because at the moment I still think there are some players who are controlling too much in this space and I think the research community needs to again come together and you know realize what the tensions are and how do we overcome them and get the people who aren't in the room in the room so that we can address their barriers too but yeah I agree nice nice talk John Dave Kuchelko from Artifacts here I'm curious to to ask are there any funders in the room come join us at the front because I wish there were more of you because it strikes me that funders governing they govern the entire economics of the of the overall research ecosystem and and and I take your change your change management points there there needs to be a bottom-up set of collective activities but there also very much needs to be a top-down top-down drivers and funders are in that position to affect change here and they have every incentive to do so why haven't they why haven't they acted more aggressively and sooner that's a really good question and honestly I think this is part of our collective problem as you know the open access or open science community and that we've just completely failed to engage them on many levels like you know it's been 11 years now since the NIH policy came into play and that was groundbreaking but since then you know that was really progressive for its day and now you know funders seem to just be it seems like everyone's yelling funders are the ones with the power to change this but then we never invite them to the room or we never go out and speak to them um you know the fact that there was only one here you know please everyone go and mob her at the back at the end of us and tell her what you want um I really wish there was more cross stakeholder engagement and not not just with funders as well you know I want more librarians in this space too because librarians again hold a lot of the purse strings in in this space especially now in Germany um they're opening up millions and millions of euros you know after saving all this money from wasting it on Elsevier and they have so much to spend it on including all of your projects so I want more librarians to be here to engage yeah and as well as I you know we should have the big commercial publishers here to defend themselves you know I don't want to just speak to an echo chamber I want people to disagree and I want disagreement from across all the spaces so that we can find out what we don't agree on and what we do agree on and move forward from there and more funders please god yes organizers get them more in the room all right uh it's one more okay it's what one and then we continue oh I have to be sure do I whoa that's loud um yeah I agree with all of this and I wanted to share two things one um I actually did a talk at STM last December on the concept of resilience and resilient systems which is not the normal thinking of resilience but um when it comes to change or okay it comes from ecological research and if you look at systems whether it's like a pond or human systems they all tend to function the same type of way and when you have highly highly resilient systems can be great because they can withstand change but they can also be very damaging because um like Japanese knotweed or something can be very hard to change something and this is my view of the scientific ecosystem is that you so it's just pulling together a lot of these threads that you've got you know funders publishers librarians researchers academic institutions obviously incredibly important for changing incentive structures the platform providers the startups and even though no one I think is wedded to certain ideas like I don't think publishers actually give a fuck about sorry I don't think publishers actually care about the impact factor really that's again not the it's not no it's not the cause of what they care about you know even if you want to look at elsewhere it cares about them I'm just going to go down this route actually um anyway so first up like you need to in order to shift the ecosystem you do have to get all the people in the same route um and in the theory you get different levels so you've got the one level which is also social um scholarly publishing ecosystem and you've got the levels above it and the levels below it so you want to mobilize the individuals within but you've also got to change the um kind of higher level uh things like on the governmental or policy level so what I'm really saying is that you should go and check out like resilience theory and think about it in terms of scholarly publishing and the other thing is that Daniel Ropers of spring and nature did a interesting talk at the frankfurt book fair recently where he said um he's yes here of spring and nature he was saying that really the uh decentralization as it were ironically of um uh public of academics um and the fact that you've got such um distributed um systems of people all over the world and no single like negotiating power has allowed publishers to get too much power which is quite an interesting thing for the ceo spring and nature to say and I feel like the willingness to change and find something else is there um and so what we want is this to be one node um but to go out and find all the others and uh work together to make the actual change sure so I think there are two points that one about ecosystems and one about incentives for change so like regarding the ecosystem I would love someone like a phd student maybe the hig one day to undertake a project where they actually visually mapped the open science ecosystem of a scholarly publishing ecosystem like the players what power they have the financial flows the communication transfer which happens and actually sort of map that out and then we can figure like where little like levers and things are and gears are that we can change to actually move things because you know like you said there is a system of inertia at the moment and very strange relationships that are very difficult to understand and I would love someone to sort of try and map that out to figure out how we can actually begin to change as an ecosystem because you know there's a lot of parasitism happening at the moment a lot of mutualism as well um and I just think it'd be really great as a project where's zenka go and get a grad student to do this for you um and I think that's a really really great idea and it's a great analogy to work through um regarding spring and nature in the ceo yeah he's a bit of a liar so I don't know if anybody saw the recent spring and nature at IPO where they talked about things like how they were going to inflate the impact factor to increase the value of their journal so that they can increase the apcs and the researchers were like um are you kidding me that's sort of like the antithesis of what everyone else is trying to do and then the ceo came out was like oh you weren't supposed to read that that was supposed to be for potential shareholders and then the IPO failed and we all left so again I don't think what spring and nature want is inherently what we perhaps want as the open science community or the blockchain community that's for you to decide again like who do you want to work with and why all right thank you very much john for this um so as you see um Zürnke just kind of forked the chain and put it now on my neck uh so uh I will be uh tearing the next session and also including this talk now this is just the last talk uh before the coffee break I'm very happy to introduce Alexander Sokolovska from the uh Validity Labs uh which is um a crypto education company in Zug and um she will tell us um how we can actually use blockchain uh very well in science and yeah I'm very happy that you're here I'm not speaking very loudly so it's good to have a microphone uh good morning everyone and thanks for the introduction I'm working for an eth spin-off Validity Labs it's a company that is specializing in development of decentralized applications and I will spend the next 15 minutes before your coffee break on um the crisis in research and what kind of opportunities we actually have now for collaborating and making a change in that space so the issues today were already covered pretty well like such as the open science why is the science right is uh it's not really it's really open why do we have a productivity crisis I'm sure every one of you have their own personal opinion and experience in all these spaces like why we don't really have a fair metric also for research impact etc so I'm not going to go through it but um I would like to focus on one particular issue that I think is very relevant and very important and that is that science has actually been going through a transition of 30 years so with this case of the US funding you actually can see um how as a function of time the funding was coming into r&d um that includes academic and non-academic uh research the sector and how the funding with the green line uh was coming was federally funded that is government and uh then the business is a blue line so you see that in the past 30 years the the funding coming from the government has been decreasing dramatically and has been overtaken by the business interests and the business input and uh you know given that we have two types of research who have basic research and that is the one that is actually contributing most to our advancement of knowledge and most groundbreaking discoveries this 50 percent of that research is being done by academia but the funding for that is extremely disproportionate so businesses tend to rather funds apply to research this is also of course important but um it's it's not in the interest of businesses because to translate what we have in basic research it takes about 20 30 years to bring into the marketplace so basic research is extremely disadvantaged and to make matters worse we all know that the number of papers is a function on time this whole uh this looks somewhat like this but at the same time the number of companies that have r&d departments uh that are publishing is actually decreasing with time so the science and the contribution of from them to science is being decreasingly open year by year so what's the natural solution to it and how can we so in a way save basic research well we have to force governments to put more money back into basic research and fund academics that are struggling but this is not realistic so social scientists and economists say that the solution to it is to align industry and academic interests so to try to find a way that we can collaborate together but let's not kid ourselves right I mean already in the 40s people came up with the concept of norms and science so those were four principles that scientists agreed are extremely important for the science output and that is communality so sharing ownership of all the data as a human race that owns our scientific output we do it for for everybody we have universality and that means that these findings should be judged based on the merit and based on their quality we have this interestedness which means a work should be free of self-interested motivation we shouldn't be pursuing wealth but knowledge and skepticism so even if we spend years on our research finding we should still be able to evaluate all the evidence and if this evidence contradicts our body of work we should be able to say we were wrong then there are counter norms and the counter norms are if you look at it and if you're still with me at this point they they are much more applicable to the business sector so this is the fact that we need to protect our our priority in publishing or a priority in filing a patent it's particularism and that means that it's a lot easier with all the papers that are coming out of there it's a lot easier to judge the quality based on the reputation be it the reputation of a university or even a research group rather than actually look at the quality of the of the paper output it's self-interestedness because their funding is so scarce that we are finding ways to game the system right and we compete for funding or recognition or for money and then dogmatism because we spend so much time investing investing in promoting our own work not really thinking so much critically about ourselves and the funny thing is that social scientists were looking at these two norms and in scientists today and they were finding that scientists were rather reporting that they follow themselves norms in science but everybody else follows counter norms so given that business interests are driven by these counter norms people are trying to experiment with technology and try to find some solution that will actually resonate a lot better with norms and provide the right incentives because the counter norms are driven by the wrong incentives and that's in my opinion scarce funding so four blockchain characteristics which come to play they resonate very well with norms just think about decentralization the fact that you try to spread power and influence over a appears over your many peers and that foresters communality this this intermediation that is if you remove the structure that with its reputation you know gives a stamp on the paper that this is a really good work this fosters then the universality economic incentives if we manage to build a system that is going to have right incentives in it and will give more power but also money maybe to the researchers we will be fostering this interestedness and then transparency of course if you open up if you show exactly what you did step by step display your entire workflow you open up to scrutiny and you foster skepticism so this is one of the examples that was done by our CTO Sebastian and by Martin who's co-organizing this conference it's about a research pipeline I don't know how well you can see it but it consists of three parts number one is the acquisition of data in experiment number two is doing a pipeline research pipeline analysis and then three is interpretation and what you can do is you can put that data on to the interplanetary file system then you can also notarize who did what so you have on top the first part was done by an operator second by analyst and third by publisher so in this way you contract the entire pipeline you can actually give people credit for what they have done is this the right solution is blockchain the right solution everybody to the day who was speaking we're saying that we don't know right so finding out will take a certain degree of experimentation so we decided to test uh three hypotheses and that is number one the solution that we're going to find will be propagating well and is going to be sustainable this is necessary for it to make sense right if we first of all educate people and educate them across many um relevant key players that were mentioned before in the question session uh about the blockchain technology what really can do and what really cannot so people don't have some puffed up expectations and b we need to raise awareness about issues in science I'm sure now you're a very uh educated crowd you know about these things but if you ask phd students or postdocs at the department everybody is unhappy about the situation they would like to change but they feel that they're alone and they have zero impact they can make zero impact if you convince them that's not the case you can actually use use their power and use their use their resources now the second hypothesis is that we will find better solutions and they will be found a lot faster if we combine uh interdisciplinary expertise of many people at the same time and the third one is that the transition between um the current state of the art into a new kind of scientific ecosystem will be um a lot more effective if we do it simultaneously among a number of key players in this ecosystem and that's what we call seeding so the method would be what we discussed also during the questions that we really it's really important that we invite to the whole discussion librarians funding organizations publishers executives investors policy makers technologists researchers and whoever else is involved in the whole infrastructure and they have to at the same time be able to in this kind of the same decentralized way make the further step now we put them in Davos in February into the place that hosts an annual world economic forum meeting and they will be for the first two days first of all discussing the whole problems and bottlenecks in the collaborative research space that we made a word of them from the perspective of also not only open science but also economics of science and then we will train them about blockchain mechanisms governance um economics and also a little bit development then we'll also show a number of applications in research and industry to so that they get a feeling like where it is applicable and then for the next two days they will be subdivided into groups based on their interests where they would like to contribute the most they will be given mentors from those areas and they will be also given design thinking experts and over the next two days they will try to come up with strategies for the implementation of new not blockchain backed solutions and maybe tools in this way we will create new ideas people will be able to pitch those ideas on stage and the decentralized autonomous organization that they will become a part of will be able to pick the best solution in their opinion that's most actionable and the winners will advance to the incubator the next three months is going to be an incubator this is our team and Tsuk and the crypto valley in Switzerland and we will be there and the teams will be working with us remotely so the whole three months will be developed will be um sacrificed for the development of proofs of concept and the teams will have a freedom to make their commitment so they can if nobody in other words has time and wants to become go to the next stage we'll still guaranteeing that it will be executed and we will build it all of our solutions will be open sourced that means we foster the commonality principle of norms and science and the whole point is that after this experiment we want to push a little bit more the whole the whole system towards sustainable blockchain backed but networks for collaborative research or norms and science and that means not only incentivizing collaboration and openness and science but it also means trying to find a way to reward risky projects to fund basic research perhaps as well and to primarily empower the community because you know what there's the situation is so dramatic that research now says that most brilliant people in the academic system that's PhD students the very young ones 33 percent of them are at the risk of the common psychiatric disorder that situation is not dramatic what are we doing so Isaac Newton has written a letter to his collaborator and actually that collaborator his opponent if I have seen further it is by standing on the shoulders of giants and I really hope that in my lifetime I'm going to see that philosophy in that principle being widely adopted in science and I'm going to be here until Wednesday um including Wednesday so please do come to me and ask me anything if you want to participate in that program sponsor or volunteer whatever ask me about astrophysics because I'm an astrophysicist do that and otherwise thank you very much for your attention thank you alexandra um are there any questions I maybe I can ask well so I liked uh I mean in response also to the talk of in the beginning uh I mean I I think the solutions in the end also this experiment that we did with Sebastian I mean it's very simple right so I mean how do you think this Tao will be working out I mean what's the idea behind I mean because there's a challenge that people may just find it overly complicated or burdensome to engage in this um so actually becoming a part of the Tao is going to be extremely simple people will do it will walk everybody during their training through it and you will have a possibility to vote on the teams that will be pitching in the end their ideas but it won't be and I think it's overly complicated I think even building your own very simple Tao is basically a couple of lines of code and we will also show it during the steps um on Wednesday during during the workshops so it's it's a place where lots of companies are driven to in Switzerland in Zug it's partially because it's a beautiful place in terms of tax perks it's pretty low um but yeah so a lot of a lot of companies go in there it's also Ethereum Ethereum Foundation has their um headquarters and uh yeah we it's just a place where a lot of companies are and it's booming and you basically walk into the city and you see already left and right everybody's basting blockchain all over the town so that's why it's it's it's getting this name of being a crypto valley kind of like a silicon valley equivalent but for the crypto crypto world so just uh I wonder how far are we away from um um a status quo where I can set up my own smart contract or DAO with legal brick like tools so I want to have the benefit of what you described without having to dive into technical details like solidity which is I hope understandable and and I would like to know from you what what do you think about this how far are we into this direction that we have this Lego brick like thing that we can actually do stuff it we're actually very close so there are a number of projects that are trying to integrate different kinds of platforms so that you can very easily either build also your DAO decentralized autonomous organization or maybe you can incorporate um a couple of tools that are not off blockchain but you can build them together and give them kind of the back end uh in a lot easier way right than being able to know solidity and all the but having said that it's also not very tricky like the whole coding and the whole smart contract that you can write can be extremely simple um yeah but there's lots of projects and I think like one of the things I to refer back to the conversation before like why do we need blockchain at all I mean let's think about it like we in order to fix science and fix these incentives that we talked about why even though there's been 20 years of right of campaigning for open science like still scientists even though they have open access journal they don't do it open access it's because it's in our culture it's because we're driven by very scarce funding and competition so if we could leverage the fact that there's a lot of money and a lot of attention and a lot of people actually are very interested in the topic if we use that momentum in order to help our basic research I mean this is this is amazing and we should discuss it nevertheless I know that there are equivalents like peer-to-peer whatever but you need to move people collectively at the same time to make a difference so why won't we use the fact that we're just giving it right now on the plate great thank you very much and maybe just to add why don't we add some science fiction to it right too and so I think that's a cool way to go and with this we are closing the session and we extend the break a bit so there will be half an hour break and we will again meet here at 11.15 okay test test okay cool so Okay, so I think we should get started now with the session. And the first speaker that I'd like to introduce to you is Professor Ali Sunayev from the Karlsruhe Institute of Technology, where he is at the Institute of Applied Informatics and formal description methods. Thank you. Thanks, Martin. So hi. It's great to be in Berlin again, and I already kind of see the vibrations in the room are quite different to those I'm familiar with and more scientific context. Scientific conferences are a little bit more different. So that's why I decided to make my talk a little bit more different. And yeah, just please feel free to ask any questions at UniGid and talk if you don't understand something or so. And yeah, Sunayev asked me to introduce you the core underlying technology of blockchain, the distributed ledger technology, and to show you the kind of most popular example of blockchain Bitcoin. And I also would like to say something about decentralization, about the transformative impact such as technology has on us as individuals, as organizations, or even on a societal level. So where are we standing right now? Well, sometimes I think with blockchain we are right now somewhere we were with the internet like 30 years ago. So 30 years ago almost nobody was thinking that internet will become such a success story. And this is what usually I'm kind of hearing if somebody talks to me about blockchain. And what is actually blockchain? Well, I have a definition for it and I will introduce it in more detail later, but it of course promises to be disruptive technology. And disruptive technology means that you don't have a problem or a use case and you find a solution to, but you have kind of a technology and then it is finding a solution. There is a bunch of examples for it and if you want to hear more on disruptive technology just let me know because I was so lucky to spend some time in Boston at Harvard University where I kind of met Clayton Christensen who introduced the disruptive innovation theory. So I'm really familiar with it. Okay, so probably most of you know blockchain because of Bitcoin. And I will go quickly through this and I don't want to speculate about who kind of introduced it and who is actually the guy Satoshi Nakamoto. But from the technological point of view we had distributed databases and even digital currencies a long time before Bitcoin or blockchain came into existence. So what was new? This guy, or the organization behind this name or I don't know, this guy solved two problems. First, he solved the so-called problem of double spending. You could not spend the same digital currency, the same token, twice or more. And second, he introduced incentive mechanisms to participating parties. So why should somebody, why should somebody provide computing and storage power to kind of run this database? And this was the crucial thing. So what is actually blockchain? Blockchain is a, sorry, I'm a professor so I kind of like always like definitions. Blockchain is a decentralized peer-to-peer database that consists of a network of computing nodes. And this database stores an immutable chronologically ordered and transparent history of transactions. And transactions store the information in a chain of blocks. That's why the name blockchain. This all is kind of, these nodes, they kind of use a very clever consensus mechanism that is based on game theoretical thoughts to negotiate what is actually included into the database. And here you see a figure on how it is done with Bitcoin. So we have some, okay, you don't see it quite well. We have some kind of nodes and they somehow decide on what is the current state of the database. And if a new block is added, it is always time-stamped, chronologically ordered. And these blocks refer to each other. And every block consists of a number of transactions with a time stamp and with the hash values of the previous block and the current block. So I guess everybody is familiar with the hash function. Math, math is really beautiful. And hash function is great. So you can have any text, any length of any string, any letters, any numbers. And with the hash function you can produce a kind of well and specifically defined length of a string. And then you can make it more kind of hard to compute this function if you kind of say, okay, the first numbers of this resulting hash value should have like three O's or so. And I know that Ismail will give a talk just after my talk and he will introduce the consensus mechanism more in detail. So I'll skip this. I'll also skip the findings because this is what Ismail will talk about. I want to concentrate on different things. And of course it uses public key cryptography. This is also kind of a math that every transaction consists of the sender, the receiver, the Bitcoin value, the time stamp and the protocol of the Bitcoin. And it is signed with the public key of the receiver and the receiver can kind of authenticate himself that the transaction belongs to him or otherwise if somebody is sending the transaction it is signed with an own private key so everybody can really authenticate that it is coming from the right person. And here you see everything in one figure. The figure is quite complicated, but the most complicated figures are actually the best ones. If you understand them. So first, this is the first step, the green one. It is validated that there is actually a registered sender receiver. Then it's validated that somebody really has some tokens to kind of transfer them. And if it's validated, if the transaction is validated, it's coming in so-called memory pool where the transactions are waiting to be stored in a block. And as soon as a new block is created, the block is added to the blockchain and distributed all over the network so all the nodes have the same information. And there is also so-called unspent transactions. So you may have some bitcoins that are not transferred to somebody else and they are also stored in the blockchain in the list of such unspent transactions. So the core idea here is that algorithms rule. So that's why we are speaking of the so-called zero trust. That you don't kind of need any persons or organizations you trust to. You trust an algorithm. You trust in math and cryptography. And it's becoming even more interesting with the so-called smart contracts. So if you have processes that are well-defined and that all participating parties agreed on and these processes are atomic, it means they don't need any human interaction, then they can be automatically executed upon fulfillment of specific conditions. And this is great. This is where the innovation is. So we have a new way to store, to process and to use information. And you know for programmers out there, Bitcoin is maybe not the best example, but smart contracts can be very, very powerful. So you can build loops and loops make fun for programmers. All the software you know, probably you know, all the software uses loops. So it can be very, very powerful. You can automate any process out there if it does not need any kind of human interaction. So what do we have next? Of course, we have databases, distributed databases, blockchains, and all of them have their advantages and disadvantages. I know that you are all familiar with kind of different ways of kind of designing a blockchain. But what I want to say is that blockchain is actually not a silver bullet, especially if you're thinking of open science, and that's what I actually wanted to talk about today. And I prepared this slide for it. If you have an environment where all parties trust each other, blockchain is probably making no sense. Blockchain does not solve the cap theorem. Cap theorem says that a distributed database cannot achieve consistency, availability, and partition tolerance at the same time. So it is always a question on trade-offs, like with the movie about fiction, with Samuel L. Jackson, the life is full of trade-offs, and the same is with blockchain. Think of security. It is always a trade-off between availability and confidentiality. Blockchain, it is always a trade-off by designing a blockchain, whether you want to have performance or security, whether you want to have anonymity or flexibility. All these design characteristics, what kinds of this mechanism am I going to use? What about scalability? What about throughput? Guys, even using... So if you decide to go for distributed ledger technology, even using a blockchain is a trade-off. Because in a blockchain, every block has exactly one predecessor block and exactly one successor block. But there is concepts of TLT where blocks may have multiple predecessor blocks, or multiple successor blocks, or where you don't have blocks at all, where transactions directly refer to each other. So it is not kind of... It is IT. It enables us to do something. And that is kind of the core of what I wanted to talk to you about, about using this technology for open science. And for me, it's a question of two sides, of system design and of participation. System design. We researchers often deal with sensitive data. Think of life sciences, medicine, genetics. This is very personal data. Or think of, I don't know, think of economics or social sciences. It may... People work with sensitive business information. Blockchain, as a distributed database, retains benefits like reducing or having actually no single point of failures and improving availability and integrity of the stored data. So it allows us researchers to store and to protect sensitive data in terms of security and privacy. Better than ever before. It's not only a question of security actually, how to keep data secured from unauthorized access. It's also a question of what we call information privacy. What information is stored? Where is this information stored? Who uses this information? For what purpose does one use this information? These questions have to be answered. And blockchain may allow us to do so. Why? Because we scientists often rely even on participants who share their information with us. Think of, I don't know, data donors in genetics. Remember smart contracts? With smart contracts, these data donors are able to determine, to decide what of their data is used for what purpose. So if a data donor cares about one disease, cares deeply about one disease, they can decide to share their own data with researchers who work on this disease. And none of the donors' data with others. This is what blockchain may enable us. So it will lead to a higher involvement of research participants. At the same time, blockchain is not designed to store kind of huge data. You know, big data. If I stay with genetics, think of omics data. That's just tens of gigabytes of data. Data size is a real problem with blockchain. Nowadays, we use kind of hybrid approaches. So we store data in a cloud, and blockchain allows us to control the access to this data. This is of course a step into the right direction, but there is still a long way to go. Next, we spoke about open science environment. Yes, our research culture nowadays kind of forces us sometimes even to have data silos. We really often have data silos in research. Okay, it has something with things to do with how we as researchers are evaluated, how do we get our stuff published, how do we get funding and so on. But blockchain may lead to a real open science environment. So in its true in sense, because it is kind of, you know, through this decentralization, it leads to kind of democratization. That the access to research and to research data is kind of getting affordable. So it will not be probably completely for free, but will be for sure cheaper and easier to access. Okay, so and the core thing here is that we have to look beyond the IT value. If we have a new way of store, process and use information, it can lead to a completely new way of data and process management. And this is something very, very crucial. This helps us to leapfrog to kind of a next decade of using data and providing data in a scientific environment. And you know, I introduced my talk. I started my talk with the quote of Bill Gates regarding Internet. Internet is nowadays criticized. And it's criticized for some good reasons. And blockchain promises kind of to solve some of the problems that are criticized right now if people talk about Internet. So what I want to point you to is this transformative value of technology. So I actually don't care about technology. I love technology, but I don't care what kind of technology it is. If it's blockchain or something else, I don't care as long as it affords me to do something. And transformation is a process. And every process produces winners and losers. So I think that what we should discuss in this room is how can we take care of this process that it is run the right way. And guys, before I conclude my talk, I would like to say that if you want to use blockchain, think of three things. First, if you have a decentralization, if you have kind of distributed nodes, then you can go further. Second, if you have kind of intermediaries or if you have somebody you don't trust to, okay, then think of blockchain. And third, if you have processes that are well defined, everybody agreed on, and that can be run automatically, also think of blockchain. So if you guys kind of have an idea but don't know how to realize it, come and talk to me. If you have money and you want to do something good in your life and even become more richer, come and talk to me. Thank you very much. Thank you very much for this great talk. Are there questions? You had your two colored blocks and one was participation. You really didn't articulate what that new participation was and what peer-to-peer or blockchain could maybe do. It doesn't do today for science. Sorry, sorry. So with participation, I meant that through blockchain, we get even more data to do research so that participants are encouraged to share their data with us because they know what happens with the data. First and second participation was about the creating a real open science in the world. That it is encouraged to share their own data with others through blockchain because you can get some intensive mechanism for it. So even for people who are kind of sharing their data for research, that's what actually all the blockchain and genomics platform coming from Yes are doing. You actually can get money for it. Okay, what I didn't mention, it raises, of course, a lot of ethical and regulatory issues. So that's why I was talking about blockchain. It's not only an IT question. But you know, with regulatory, they always need some time. So first we had cars and then we designed and defined rules how to move them and so on and so on, what is allowed and what not. So they always need some time. That's what I meant with participation. The raw data used in science as well as the science results are big enough to store in blockchain usually. And you just said that we are going to store them somewhere else and use blockchain to give access to. But usually where we store those data are going to be a place which is going to be central authority like Google or Amazon who's going to store these in their heart. So how do we ensure that in this workflow the pure decentralization happens and then somebody just gets the idea of the data set and the whole blockchain process is out and then we'll just log in and get the data. I'm trying to get the link. So unfortunately I can't predict the future. I wish I could. I can't. So I don't know if you'll be right. But right now we are using hybrid approaches, yes, because if these are really huge data sets, they are stored in the cloud. As I told you before, blockchain kind of is giving you control who is allowed to assess the data. So the future research will be for sure about how to make it possible what kind of designs are for blockchain. How to make it possible what kind of designs of a blockchain of distributed literature technology make it possible, always a trade-off to deal with bigger data sets. And maybe sometime in the future we will have such a setting where even kind of huge data may be stored in blockchains. You know, it's not always a question of computing and storage power. This is actually not a question. The question is how can all these nodes decide and how can this database be really distributed and stored on different nodes? But we will do this. I don't really kind of worry about this because we guys, we IT guys will not only have to do for the next years, but I think we will find some answers on these problems to these questions. But you know, you mentioned kind of these big companies that kind of rule internet. This is the way it goes. You know, they used a niche. So as introduced, as internet was introduced, and internet is not only kind of worldwide web, internet has more services. It's email, it's FTP, it's voice of IP, name it. Internet wasn't, so let me, let me, let me start different. I talked about this yesterday evening. There were countries in Africa that didn't have a functioning banking system for decades because they didn't have a bank on every corner or not such an infrastructure they have in Europe. But with mobile phones and not even smartphones, you know, they, through SMS, they could transfer money and then they got a functioning system. So internet was not designed for e-commerce stuff or for digital currencies. But this is what disruptive innovation is at. But people learned how to use technology for new cases. So with big ones, you know, do you remember a company named Nokia? They were quite small and then the guys, the guys were very smart. They decided to move on from, I don't know, shoes to refrigerators and from refrigerators to phones. And then it's not as easy. You know, Apple was also not doing very well for quite a while. And Microsoft was not very popular kind of a decade ago. You know, a decade ago all my students wanted to go to Google. Nowadays Google is the evil. So it changes. I, on my own, celebrated Research Gate a couple of years ago. And now it's on the dark side if we're talking about open science. So, you know, I don't know what the future will come but that's what I want to point you to. We, if not we, who should take care of this process, because we understand IT and you guys understand the world outside. So if we connect, I think we have quite a good chance to do something. Yeah, I have a question which I think builds very much on what you just said there because I see the word decentralization in the title talk, which sort of, I am always missing the sort of elephant in the room which is the main property of blockchains which emerges from that and that is uncensorability because two of the five properties of blockchains are immutability and decentralization and the emergent property of that is uncensorability which means blockchains cannot be censored. And this is something which I frequently miss in these kind of discussions. So what about the implications of something being not censorable? Can you speak to that? Well I can, but it's like, you know, just my thoughts. That's nothing which is... It's a little bit like with the printing press in the Catholic Church because they wanted to censor the printing press and couldn't and it was of the devil. So I must be careful if I'm speaking about religions. So you know, if you, actually if you want to get really, really rich I wouldn't even go for a kind of blockchain stuff just to kind of establish a new religion that's probably the way to get very rich. So about decentralization. So for blockchain, as I told you, it's a question of design. So there is also permission blockchains and they are running quite well. So think of hyperledger fabric or so on. So they don't have such problems with throughput or energy efficiency like Bitcoin has. But they are not scalable. So it's always a trade-off. So with the definition of blockchain as you... decentralization is a core idea and your point is actually the same as what people speak about that you reduce intermediaries. Because you know, this kind of... It's a core feature. Uncensored ability. Absolutely, absolutely. Yeah, thank you for your presentation which you started with Bill Gates and many times you come across papers and people who say and claim blockchain could be the next generation of internet in a sense. And linking to that point, I would like to hear your perspective. In what ways could blockchain be this sort of second generation and what could it offer what the general internet we're using now is lacking from? So I could speak about this for hours. So you know, actually it is not a new internet. We're still using internet technologies. So we kind of have a common sense what internet technologies are that we rely on them and blockchain relies on them. But what internet kind of introduced are these big parties that got big because they had access to data and they kind of store it in a certain way. And that's what actually blockchain is about that this will decentralize it. But of course there will be parties who run, who kind of run this database. You know, not only in permission in kind of open blockchain. So for Bitcoin, you know, there is intensive mechanism. But that's not kind of that everybody or faster runs a computing node for it. But the core idea is that we kind of move from this internet of information that what people are speaking about to internet of value. That you not only kind of store information but this information has value. Like in Bitcoin, you know, there is kind of this digital currency but it's not endless. It's a predefined set of Bitcoins available out there. That's why it's getting value. Because there is an end. You can't kind of just print more dollars. You know, print more Bitcoins. That's algorithm. If you trust in it, that's what algorithm provides. But with this, under this tokens, you can kind of hide values. And it's not only Bitcoins, so there is kind of, you know, other ideas. You can even kind of give a token a value of your house or something. You know? So there is, there is, there is for sure, and that's what I told you before. There is for sure a lot of opportunities and possibilities for us also as researchers to shape the future in the way how we use this information which is becoming value in the future. And we will see what use cases will arise concerning of this. This for sure a new way, as I told you, a new way to store the process and to use information which is also value. Fantastic. Fantastic talk. I just wanted to pick up on what you were saying about giving people control of their own data. So I work in sort of human, like cognitive science, human research. And one of the issues that we find talking to patients in our research is that there are concerns about open science, real concerns about open science because currently if you take part in research you have to consent, right? So you either essentially give consent for your data to be shared and then it's open and anyone can have access to it or you don't share it at all. So there's this sort of tension between the rights of people taking part in research and open science. And if we can find a way to solve that by giving people control of their own data so they can say, I want my data to be used in this but I don't want it to be used in that because I'm concerned about the consequences of it or I think that could be huge. The most interesting part is here that if you kind of can control who is able to assess your data you can change your mind and you can kind of, you know, sometimes we don't know what technology will be able to do in ten years even with the omics data. So if you right now are okay to share kind of your genome data with somebody but in five years, you know, oh, this is maybe something I don't want to have not only because of me, because of my family you can change this control and coming back to the question of data size and the blockchain, there is research on, you know, there's also, so in science, I don't know, in medicine, Zernke is a physician he probably knows best. He's obligated by law to be compliant with all this stuff. They have to store pictures for 30 years. This is what I mean with Open Share because, you know, after 30 years there is research on this Genesis block, the very first one, that everybody decides on the state of the new Genesis block because, you know, the information after 30 years you don't need it. Then you can kind of decide what kind of, you provide a new Genesis block and start from you and then it reduces data size and if we speak about open science I see that there is a lot of cases in here so it's about data sharing. It's also about how we are evaluating ourselves as researchers in all these age indices and so on. It is also about how to get people participating in science. It is also about publishing and all these publishers and intermediaries. So, and these use cases are quite different because it's, you know, the problem, the real problem is always kind of a detail question. So it's quite easy for me right now to talk on this level but if we start really to do so and we do it then it's become complicated because then you see a small problem which is a detail question. We are not thinking right now. So, and what, am I talking about this? It's always a trade-off and it's always a design question. So before you kind of start building a house think of how many windows you want to have where the door should be and so on how should we define them. Please talk to us because we observe a lot of solutions out there that kind of say we are blockchain they are not blockchain at all if you take a look if you take a deeper look or they are taking the wrong design for the wrong, for the context. So it is very, very, very tricky here. Be careful. Thank you very much. Thank you. Thanks, we're moving on. So Ismail Kofi is the next speaker and he seems to be doing a lot of things but so we keep introduction short so I just say that currently he's working at Tendermint and he's going to talk about scaling solutions. Not only, okay great. Oops, can we start from the beginning? We got the rundown on my slides. So good morning everyone. I'm Ismail Kofi. I graduated in mathematics at the University of Bonn worked at several companies and in applied research institutes such as Fraunhofer and was very interested inspired by the Snowden Leagues on privacy preserving technology and decentralization and from that I started working at EBFL as a software engineer where collaborated on scalability research on blockchains but also on distributed decentralized systems and privacy. So this work inspired me to join Cosmos and Tendermint which are also briefly introduced in this talk. So let's start. First I will reiterate some basics that are necessary to understand what is this blockchain thing we're talking about. I will present some challenges. One of them is scalability that's already mentioned but there are much more challenges in the blockchain space or many problems that need solving that I will just briefly present and then I will briefly talk about scalability and present one scalability solution which is not just one solution for scalability but basically an ecosystem of solutions that I will explain. So to the basics what is a blockchain? As you've seen there are many different definitions. This definition serves the purpose of my talk the best and it's also very simple because it's just a sentence but there's a lot to digest. So a blockchain is a deterministic state machine replicated on nodes that do not necessarily trust each other. So what does it mean? A state machine, you could think of a state machine you have several states and transitions to this state you have an update function that takes the current state and a transition and updates to a new state. So in the context of blockchains this could mean the state is the account balances and the transition could be a new block containing transactions in a certain order. So this state is not stored at the central server or central service but is replicated on nodes and the tricky part is these nodes do not trust each other. So how do the nodes actually reach agreement on the state if they don't trust each other? So this leads us to consensus. Consensus algorithms are or consensus protocols are the tool that makes it possible for these nodes to reach agreement. There are two types of consensus algorithms roughly one that assumes that nodes can only crash they are heavily deployed in cloud infrastructure for instance if you use Google or AWS your data is also replicated it's not stored at the single server but at many nodes but it only assumes that you are in control of the nodes so a single entity is in control of the nodes and you can trust those so it only operates correctly under the assumption that those nodes can just crash and the more interesting part for blockchain or for nodes that do not necessarily trust each other is that these nodes can behave completely arbitrarily they can expose malicious behavior often called Byzantine behavior coming from a research paper that tried to solve the Byzantine generals problem where generals that communicate through a messenger try to reach agreement if they should attack a city or not. So examples of these are PBFT and tenement tenement I will roughly explain later so consensus can operate in different timing models on the very left we have synchrony which basically means there is an upper bound for an unknown upper bound for the message delay for the message to arrive and there is complete asynchrony which means that you don't know if there is such an upper bound there is no such upper bound and messages could potentially be delayed forever so this is more or less how the internet many protocols on the internet come with this assumption and then a very simple way to explain it if you think of synchronous communication is more like a phone call where you have direct feedback on how people interact synchrony is more like writing an email because you write an email, you send a message you never know when the recipient will actually read it and in between those there are different timing models semi-synchronicity and partial-synchronicity I'm not going into detail there but it's interesting that there is also a middle ground that is interesting to explore if you want to learn more about consensus I can highly recommend this podcast I just linked there historical overview on consensus algorithms and explains them in more detail so now a few limitations on what you can do on distributed systems in general this is not specific to blockchain or any cryptocurrency or something this is a general theorem that states under the assumption of complete asynchronicity no deterministic algorithm can reach consensus under the assumption there's a single faulty node this is a very strong claim and it's important to know so what is interesting here it only says for deterministic protocols and also only complete asynchronicity timing model it doesn't work so it's actually very necessary that they explore the middle ground it sets the stage what we can actually do in consensus algorithms they have probabilistic consensus algorithms they are not impossible through this impossibility theorem another theorem that states what you can do in distributed systems is the cap theorem that was already mentioned by Ali so it basically says you can only have two out of three properties which is the properties are consistency which means if you read from let's say the database you get the most recent right or an error and availability means that you always get a reply from the database but it's not necessarily the most recent data and partition tolerance means if you have a bunch of nodes that communicate with each other on the internet what happens if the network splits and the messages between these two groups or partitions cannot communicate so this is something that happens all the time on the internet and usually if you build distributed systems you have to assume that partition tolerance is a necessary property you want to achieve so you can only trade off basically availability and consistency so for instance bitcoin that was mentioned is available like to trade off availability for consistency because what can happen there is a chain can fork nodes get blocks that were propagated through the network but they are not the longest chain that has been mined so until they get the longest chain they have to when they get the longest chain which is the extra ground truth they have to throw away all the work that has been done and then if you read before from the blockchain basically you get stale data that was not actually representing what happened so next this brings me to what challenges are blockchains currently facing so there is this idea of replacing central authorities the Bitcoin paper itself speaks about replacing central banks I think and there is a large authority and people want to live in a kind of decentral world where there is no power agglomeration on central powerful authorities why don't we see that yet why are we just talking about it and what are the challenges we are facing in these systems so one big challenge that is often overlooked is usability so these systems usually they are built by experts and they often assume that you know the stuff they know and this hinders mass adoption so often if you deal with cryptocurrencies you have to have a basic understanding of public key cryptography that was mentioned but I mean for mass adoption this is not really good because most people probably don't need to know these things so there is a trade-off to be made here as well about educating the people or building the systems in a way that you don't need to educate them this is ongoing research but I think the end-user usability comes after we have actually systems that scale but it's a very important thing to keep in mind if you build systems another challenge is also often overlooked is developer usability so if you want to build on top of a blockchain you want it to be as easy as possible for developers to build on top of that so in the past the only solution around has been for instance Zcash did that which is a very interesting project by the way they forked the source code of bitcoin changed the logic of what happens there and deployed a new blockchain called Zcash and this is quite cumbersome and very difficult to do you have to know a lot of the inner workings of the source code and everything Ethereum changed that in a way that you can deploy smart contracts which are basically programs and you can deploy them on top of the Ethereum blockchain the only downside to this is you're stuck to the Ethereum blockchain and you're stuck with the trade-offs that are made on the blockchain in terms of scalability and all these consistency and availability properties that underlie these systems so this is very cool but it comes with downsides as well this brings me to the next challenge usually if you build such systems if you think of blockchains as basically replicated databases these databases are not connected with each other at all so basically if you have value on one chain you cannot transfer value to the other chain easily and the common approach today is you go through a central exchange or you introduce a central authority again and that defeats the whole purpose of the blockchain so yeah we definitely need a way to interact with each other which does not come with the assumption that you trust a single central authority again another thing that was also mentioned already is privacy actually blockchains are not privacy preserving per se so if you think of bitcoin for instance it basically it basically you could think of it as an excel sheet which is like Twitter's and the excel sheet contains the history of all transactions in the public meaning like Ian Myers said that Defconn recently it's like Twitter for your bank account this is probably something you don't want in the context of this research community you could think of okay if I store records of data or hashes of data on the blockchain which is actually public data that's totally fine it's totally okay to store this data publicly but if you're dealing with highly sensitive medical data for instance you obviously don't want that publicly available or even the metadata maybe of that so there are trade-offs to be made between transparency which is a property that blockchains definitely have so it's very transparent but you also want some form of privacy depending on your actual use case and there's probably also a good reason why there won't be like a single one size fits at all blockchain solution that solves all the problems another challenge we're facing is how do we actually change the inner workings of a deployed blockchain so currently how this often works is there's communication out of band then people kind of try to reach an agreement somehow and propose solutions and then try to convince the community of their approach and there's actually also no transparency here ideally you would have the voting mechanism on top of the chain so it's transparent again and people can vote ideally in some form of democratic system stakeholders of the chain or community members of the chain so something that was also kind of mentioned is energy consumption so bitcoin uses as you have heard something called proof of work which is not only necessary for consensus but it's mainly also something called a civil control mechanism so civil control mechanism is it makes it difficult or impossible for a malicious actor to flood the network with fake identities and take over the majority of the network with that so in bitcoin this is done by finding pre-images of hashers and this is a very difficult task basically what you can do you must basically try all different solutions so it's an exhaustive search more or less energy consuming people use specialized hardware for that but it uses for instance bitcoin annually uses 73 terawatt hours so just to make this number a bit more understandable this is like 7 million US households or as much as the country of Austria Ethereum the numbers are slightly better but it's still loads of energy consumed there are people that argue that's fine because we can use renewable energy and things like this but the question still is is it worth it to have this energy consumption I highly doubt it but there's no clear question clear answer to this and the main challenge and the most pressing challenge we're facing is scalability so scalability means mainly throughput is how much transactions per second your blockchain can handle and latency how long to wait until a transaction is confirmed and this in major blockchains which major public blockchains are currently deployed like bitcoin and Ethereum this doesn't look very nice the transaction per second rate is very low like from 7 to maybe a few hundred at max and this doesn't scale so if the world would actually use bitcoin the system would basically flood with transaction and it would more or less stop working another thing another topic and scalability is how do we reduce the data storage necessary for nodes to participate in the network and also for clients the naive approach commonly used in deployed blockchain system is you have to download the whole chain verify all the transactions it's infeasible for many commodity hardware or smartphones so slightly more on scalability because it's such a pressing topic there are basically two different approaches or two different families of approaches one is so called on chain scalability so this started off with the blockchain debate in bitcoin if you increase the block size in bitcoin or in all these systems you can fit in more blocks but this doesn't really scale it doesn't really solve the problem because it only increases the throughput with a constant factor of efficiency as well there is so much academic research so the research community itself is building blockchains by the way and I put on the slide a few publications the name of a few publications each of which would deserve their own talk sometimes quite complex systems and the thing I want to mention here is probably in a few years we will definitely see a scalability solution even for on chain for single blockchains on chain the downside of all these approaches is again it's like one size fits all solution they try to build one blockchain of course you have to make trade-offs one chain that basically scales but still there is no interoperability involved most of them are academic projects and often there is no proper implementation but for some like chain space there is actually a company that is building the implementation the other family scalability approaches as I said there are two the other family is layer two there are off chain solutions where you take off the processing of the transactions from the chain and you merely use the chain as kind of a settlement layer or another analogous would be if you transfer money you only use the blockchain as kind of a court if there is disagreement so there is the lightning network riding if you are interested in those you should look them up in the audience people that are actually building payment channeled networks so the big advantage of this approach is that you are building on top of existing well established systems that have been around for a while and the downside is you are still limited via the main chain which is often like Bitcoin or Ethereum so throughput there, transaction costs all these things still exist often they don't incorporate interoperability as well and they sometimes introduce the risk of centralization so what if you could use you could use another scalability approach where you have many parallel chains they operate in parallel and you do the transactions on the particular chains for your particular application or use case so there are two major projects, Polkadot and Cosmos Cosmos I am going to explain the comparison of those I linked the blog post that does a fair neutral comparison on the trade-offs made there so now to Cosmos as I said it's not yet another blockchain but it tries to build basically a whole ecosystem of application specific blockchains instead of deploying your own smart contract on something like Ethereum you could also build your own application which is their own chain or other chains and with this approach we try to solve scalability, interoperability and usability so Cosmos is powered by Tenderman BFT which is the consensus algorithm if you remember so it's a perfectly Byzantine fault tolerant consensus algorithm which operates in the parts of synchronous or in this middle ground so the key takeaway here is it's very fast, it can take thousands of transactions per second and produces a block every one to three seconds so for the civil control mechanism we replaced proof of work in the main chain with proof of stake or delegated bonded proof of stake which is less energy consuming and also gives you the advantage that you can incentivize honest behavior or punish malicious nodes for misbehaving and not acting according to the protocol also enables governance so I want to highlight a little how Cosmos works and what you could do with it you could use Tenderman consensus algorithm and Tenderman core which wraps the state machine by using something we call the application blockchain interface and the cool thing here is if you're thinking of building any blockchain or consortium chain or proof of authority chain you could use this approach and basically you can use this approach and code in any programming language so if you develop a chain like this so how do we connect those chains we connect those chains for a protocol called inter-blockchain communication protocol so the details are a bit difficult to grasp for example if one chain wants to send a token to another chain it basically locks the tokens on the first chain it sends a proof to the other chain that the tokens have been locked this proof gets signed by validators of the first chain and so then tokens with the same amount get created on the other chain so it's like the very basic idea here with this you can sovereign blockchains can exchange value so now how do we connect all the chains if they exist naively you could connect all with each other this would lead to a large communication overhead because for N nodes you can think of like everyone's connected to everyone this would cause for instance 400 nodes you would already have 5000 connections instead we use the approach of a hub or hub and spoke approach where the hub connects the different chains often we call them zones the zones don't communicate directly with each other but instead through the hub where the hub itself is a peer-to-peer network so if this is not enough for you you still think maybe there's an easier approach how could I build a blockchain myself I recommend you to check out the Cosmos SDK which is a set of libraries that makes it extremely easy for you because some design decisions are already taken care of and the only downside is you're stuck to the programming language go for now we also build other SDKs soon and this is ideal if you want to build a public proof-of-stake chain and it's a modular design you can use existing modules you still have to quote but it's much easier you can learn more on the homepage I linked there so the main takeaways are many challenges in the blockchain space that are hindering mass adoption although there's a big hype scalability is the most pressing one there are many smart people and well-funded smart people that work on the scalability problem so we will probably see a solution there it's appropriate to be optimistic here Cosmos is one scalability solution that tries to establish a whole ecosystem we often spoke of trade-offs and not every application you want to build has to use the same trade-offs so here you can explore all kind of different trade-offs and build your own zones according to the specific needs you have and the cool thing about this you can also if this research continues and for instance privacy research continues you can plug in another zone that makes use of this and it's the whole system still exists and operates in the same way thank you very much I hope I didn't confuse you too much thank you thank you very much for your presentation maybe we take one question if there's a question yep the most challenging trade-off with regards to scalability so I think you always have to make trade-offs between things like decentralization security scalability basically so these are the trade-offs you have to make and I think there is no one as I said I think there is no one solution that will solve the scalability problem in general for all use cases it's more likely that we will actually see an ecosystem of different chains actually we are already seeing this but they are not connected I can't answer this question because there is no single answer to it it depends on your use case I think for the sake of time there is going to be a panel as well we will switch also Zunke kind of sacrificed his own talk now but I just maybe want to use this moment to highlight again that this entire conference is really I mean we are all sitting here because of Zunke and we should give him an applause yeah and we should have like a flower bouquet or something now but we are not as fancy yet so we can think about something until the end of the conference if you guys have an idea then just send me a mail what we should give Zunke a bitcoin maybe cool and now I am happy to introduce Bela Gibb he is a professor of computer science and just recently moved from Uni Konstanz to Wuppertal University and this is a moment in history we have to highlight that that I know Bela now for like 16 years and we met here 16 years ago because we were both winners of this context called Jugendforst which is like a science fair in Germany and when you win that and you are invited here and so we had some legendary time in Berlin but the other thing that I find interesting is that Alexander before spoke so the founder of Validity Labs is Sebastian Birgel and he is also in this year of Jugendforst winners and then with me and I guess there is one more there is four out of the 12 guys in 2002 that were at the final of this science fair that are now working kind of related to blockchain and I found it kind of a good statistic and interesting and don't know what it means that something is happening right? Very much. I suppose it means that we are all working on something really interesting so in my talk I will talk about trusted time stamping. What is trusted time stamping? Trusted time stamping allows you to prove that you had certain knowledge at a certain point in time or that you had access to a certain file and I think this is a very central question to the question of doing science and doing openly because that's where you can prove that you had for example an idea at a certain point in time. The project that I will present is not just my own project but a project from my research group that's why I want to briefly show them some of them are also sitting here so it's a joint project so the service that I would like to present is called Origin Stamp I started this service in 2010 2011 and the motivation for starting this service was that I had some student projects on our university web page. Back then I was a PhD student and I wanted to motivate like bachelor or master students to work on certain research projects and then I found out that someone like copied these ideas and a company actually then made some money with that so I was thinking how is it possible to prove that you had a certain idea let's say a master project and how can you do that and I mean nowadays I think it's very clear you use the blockchain for that back then it wasn't that clear what some people did was I can skip that now what some people did of course you could go to a notary agent or you could maybe tweet the idea and this way you would have a timestamp from Twitter or Facebook or something like that but it's not really convenient so that's why we decided to develop the service. Another possibility a bit old fashioned would be simply to describe the idea you had and put it in an envelope and send it to yourself and don't open it so you see it's a possibility it works but it's not very convenient so the service that I want to present I will give a live demo I need a live demo so if you want to try it yourself you can also use your mobile phone and what I'm doing now just try it yourself so you go an origin stamp you open the web page and it's completely free so please open originstamp.org and not com because .com that's the commercial page but for research we have this completely free web page and when you open the web page you can see here this option stamp here or you can actually also just install the mobile phone app but I think it's easier if I demonstrate it now using the web page so if you click there you have the possibility to either upload a file that could be a photo, a pdf document word document whatever or you can also just enter text here in a box and I do demonstration if I type in here test I mean we heard that before that this hash function so we the text I entered it's really hard to read but I entered test and then you see that at the bottom we have this hash that corresponds to that text and whenever I change the text here you see that the hash changes I say now stamp I would actually see that I did that before at another conference in 2014 and you can see that this text has already been entered before and the same is true of course if you upload a powerpoint file or research data maybe some data you got from your microscope so whenever you have any kind of data that you use for your research you can just timestamp it in this way to prove that it already existed at a certain point in time you can also click here on the certificate then you have all the information you need to verify this timestamp and as you can see it's really easy to use you basically just do drag and drop of the file and the file is not transferred to our servers because the hashing is done within the browser we never get really access to it over the years we offered now for even more than 7 years it has been used nearly 3 million times now and you can try it yourself as I said it's free and you can also see here that every few seconds it's used somewhere in the world okay I go back to the slides are there any questions regarding the usage okay I was just wondering like in the context of how IPFS works or this IPLD system so if I made a very small change to my data is there a way that I can link that analyze or change data to this original it's not possible but of course you could timestamp that as well so that would be the only way so it's very simple actually the way we do it we upload a digital file let's assume that you upload it a video then we just as I said gets a hash within the browser and then we do a transaction within the bitcoin network and ethereum so that we have a permanent record in the blockchain of this file and then it can easily be verified of course since we offer this service for free and we don't want to bloat the blockchain we don't do a transaction for every file that you want to hash but we like gather all the hashes of the whole day and then every 24 hours we perform the transaction we have also some extensions that you can use for your research projects for example git so if you want to if you use a version control system you can like timestamp all the source code development of course you cannot just use git for source code but you could also use git for when you write a publication for your latex file or whatever so you can really prove the state of your research on every single day we have a plugin for wordpress, the javascript plugin and also for backup solutions for timestamps, the state of your backups and we have a free to use API that's linked there for non-commercial purposes here you find some information how it works so it's all documented on the web page and another possibility is that you can try our mobile phone app it's also very easy to use, basically you just take a photo and then the photo is timestamped and you can even see on a map where it was taken so wait a second so that the people can find it later and of course it cannot just be used for for signs but also many people use it to for example when they get a rental car and they see okay there's some damage to the rental car maybe there's some damage to the windscreen then you can just take a photo and if you return the rental car a week later a company asks you to pay for the damage you can simply say no that was pre-existing damage and another possibility for example that I know people that used it when they moved into a flat and there was some damage in the flat and later when they moved out the landlord asked them to pay for that so that's another possibility let's see whether that works maybe you've seen that I think it's also it's it's a video that shows a new technology using machine learning and it allows you to the playing so you have the source sequence on the left and the artificial creation on the right and I think that's also a nice application of trusted time-stamping because we don't really know what is real and what is fake anymore also in signs so let's think about the situation maybe in 50 years we want to know what President Obama said or President Trump said and I mean everyone can just create these very, very realistic fake videos and of course if you time-stamp all this information then it's kind of preserved also for in 20 or 50 years and since more and more information is digital it gets always easier to fake this kind of information here we see another short sequence so it looks really realistic and I think in 2 years maybe 3 years we will not be able to distinguish a fake from reality anymore and I think as I said also in this area time-stamping is really important then I would like to come to some other applications another way what you can use it for is we all know these videos they are called dash cams and in court if you have a video of a crash you cannot really use it because it's not a real evidence and it can be manipulated in the meantime so we developed an app that is a dash cam but uses also this kind of trusted time-stamping and after an accident of course in a mobile phone you have sensors that can detect accidents that they can change in acceleration and then the video is time-stamped within seconds after the crash and if later you have the court hearing you can present video evidence that already existed only a few seconds after the crash so you have the data from the airbag for example when it deployed and you have the time-stamp from the video in this way you can prove that you didn't change anything because you simply didn't have the time to take any manipulations this was also just cited from Germans supreme court so it seems that the value of dash cam footage will change in the future the way it works is very simple I think I don't have to explain it here in this audience I would like to say a few words about the current users the time-stamping service of course researchers are really important to us and I get maybe one phone call a week of a researcher that used it for example when they synthesize proteins or some other things and they have some questions so they are I would say the biggest group of users but also journalists use it for example in the war in Syria I know that they have used it for cases of insurance patent lawyers and so the possibilities for using trusted time-stamping I think there are really there's a lot of possibilities okay that was my last slide do you have any questions you said geographical locations are also stored as metadata but is there a possibility also to geostamp but then the whomever stamps it has its geographical coordinate assured right is it ever possible so of course these geographic information that we include in the stamp can be either manipulated because we rely on the sensor data of the mobile phone it's more for yourself that you know for example if you were hiking and you saw I was in these mountains three years ago and I had this idea then it's maybe difficult to find it but if you know okay I had it when I was hiking in these mountains it's very easy to find it but it can be easily manipulated so it's not should not be considered as evidence I wanted to quiz you more on the granularity of your time measurements so you said you're doing it once a day but in Bitcoin the best you could do was 7, 8, 9 minutes that's fine for current science maybe but the IoT is the world of science millisecond so there's the project from Google called rough time I just wonder if you're aware of that and what innovations you thought you could implement to give you that per second time stamping at scale okay I didn't know about that project I'll look into that of course it really depends on the use case I think in the case of scientific ideas and scientific data in most cases the accuracy of one stamp the time stamp a day is good enough we also have this commercial service originstamp.com for example I think I can say BISF is using it for time stamping like things in their production and then they need a higher accuracy so we use at the moment Bitcoin and Ethereum but if you want to have higher accuracy of course it would be better to use other blockchains as well to allow of a higher resolution I agree I have a question that's a little bit related to the whole kind of mechanism of time stamping because if you have a data set and then you hash it you get some kind of unique identifier but if you want to prove say I write some code and I want to prove that I was the first person to do it and then you change a very little thing and this B equals will become A equals and the hash looks completely different I wonder are there any solutions out there for being able to prove like the similarity maybe of code or I mean what you would need is kind of fuzzy hashing in theory that would be possible but I think the easiest solution is simply to for example if you talk about writing code that if you use something like version control system you simply time stamp every commit you do and that's what we do with this plugin so each time you commit your data it's automatically time stamped so you don't have to do anything manually but it works completely automatic so I had a question regarding I found it very interesting the German Supreme Court rolled on this dash cam recording using some of the research do you have any court cases that are in regards to research data being verified because I'd be very interested in seeing if from a legal standpoint if this time stamping was used to back up research or patents that resulted from research yeah I don't know of research that was discussed in court but there are like court cases where time stamping on the blockchain I mean we are not the only ones anymore several companies that do that where it has been used in front of court successfully I can send you some information about a court case in China for example yeah I'd be interested okay I think that thank you very much and it's for free it's for free when you open the web page go on the .org not .com and I look for it like early on and we have the largest and most secure blockchain for signs already set up it's bitcoin blockchain right so what's the point of having more for signs okay yeah thank you very much okay no I want okay so I want to call up the panelists now so Vlad Günther is not here he want to like lead the panel the panel is off we changed it slightly like Ali Lombard and Ismael and can you come here for the panel please yeah yeah here you want yeah it's okay yeah we just take a seat here okay yeah so we changed it a little bit so what is blockchain and what is blockchain for signs yeah we like when we first designed the conference we were into the technicalities and now we are like more on a definition level right so we can just take a seat okay the one that didn't speak it's only you okay you just introduce you in like two lines is that okay and like how you ended up here yeah okay so hi everyone my name is Mo and I'm CEO of Celer Network working on off-chain scalability and I'm here because we just came back from the DevCon and this is awesome event and we want to chime in what we're thinking as a platform builder and how to contribute for signs for blockchain okay cool thank you very much so what is blockchain yeah that's a good question okay so we have the technical stuff we discussed it and I just want to like use it like one limitation is energy consumption yes and do we all agree with that this is like true for certain blockchain setups right I just mentioned energy consumption of the well established systems like bitcoin or ethereum it's not necessarily true if you use proof of stake for instance you don't waste energy in that way as well there are other chains or if you use a consortium or private chain where simple control mechanism is just oh this set of nodes is preset and you cannot change that well then you don't need proof of work as well yeah exactly so this is like one misconception right we just want to clean away right some the fact is that the well known established systems like bitcoin or ethereum waste loads of energy yeah and then there is like one thing people say like blockchain it will expose all data to all people all the time so it's just a design question right you can design it true there are also other projects like I mentioned Zcash for instance that tries to hide the transactions they use advanced cryptography something called ZK Snarks which is like zero knowledge proof this is also ongoing research and there are many many new interesting advances in this area and we probably will see something actually ZK Snarks is also scalability solution because you can kind of compress what you have in a succinct which like kind of means short proof what happens so if you think of state transitions you could also have a short proof like from the genesis block to the current block what happened in this time using ZK Snarks so there's loads as I said ongoing research but there's loads of things going on there and the cool thing about ZK Snarks is it doesn't only solve privacy but also scalability to some extent yes to some extent yes so we have like this there's a cap theory even the graffiti artist put it there's a triangle with a cap on top the CAP and there are a lot of people in blockchain space that want to like solve this problem but to square the skeptical triangle it would be really revolutionary if you would have a system so we all need to be skeptic but we have like several like a real world trade-offs as you mentioned exactly so which one is the best and like even the state channels on top of a blockchain system they are not decentralized right but they have interesting new reproductions here so these are so we I'm pretty fine with all the technical things that we discussed in terms of blockchain up until now right and in the beginning we had like while we need cultural changes right so where do we see blockchain in science that we can like support cultural changes in science where we have like the time stamping now well we could like also send our hashes to Elsevier right but I mean manipulated right but ok so but we have like one thing the time stamping of that there was a conference once that there was a guy who said like a blockchain the only thing that blockchain really does is decentralized time stamping of anything a friend of him told him so he was a blockchain skeptic blockchain application in science ok I think it's great and this is like a right thing blockchain does time stamping in a decentralized way and it's as good as saying the internet is only good for sending bytes around right it's as useful it's useless yeah so ok it depends on what we time stamp and what we do with the data on top yeah and I would argue that actually blockchain can offer a lot more than just time stamping and in the specific context of science and scientific research you know there's a lot of things we can do on the crypto economic side and the one specific topic that I want to introduce to the audience is something called token curated registry TCR yeah this is good we've heard talk about this and this brings us to the crypto economy right this whole new token stuff so you would summarize that on the blockchain too includes the crypto economy yeah so you know just to give a brief overview of that TCR what is TCR you can think of we will have this later we will have this tomorrow it's a perfect we will have a talk on that oh ok ok so no no no I just want to like let's talk on this ever like what is blockchain and like we would summarize crypto economy about it yeah we will have a talk on that tomorrow yeah so I would say that blockchain is a new way like there was like this thing blockchain can be used for everything and blockchain is not useful for everything you know we have like these both things like well and I think it comes do you agree with the statement it's like well blockchain is just a new way to organize all online stuff right so if you can represent something online like fashion like science like anything basically right you could do it in a blockchain way right what does this represent to you if you think of like we have centralized first parties at the moment that provide services and I want to include institutes to this that are open science institute publishers mind being archive but it's also centralized right if they shut down they shut down right so to have like let's say an open access journal on IPFS it's to me it's more open science centralized open access repository somewhere right and so to like to define what what blockchain means is that you organize an online service that we already had in a distributed way they are not such just some plugs that you can pull but you have to pull a lot to stop Bitcoin in other blockchain it's like decentralized that means that there's like no central entity that can manipulate the system and it's like it can be immutable right it can't be changed arbitrarily it can only be changed as described and it's like provable to the outside and then and then one guy from a result institute came to me well we had systems to design provable systems in 30 years but it's and then I want to like bring it to the hype it's also a hype because we are sitting talking about these things right now here right it's not 30 years ago when they had the system to make a computer system provable yeah is it okay so I'm I mean like what's your like yeah is it like so thank you so you're mixing up a lot of things I must admit that as a professor I have a strong opinion on almost all of these things you brought up so let me maybe first kind of sort it start with maybe cryptocurrencies so what I think is a lot of people are afraid of fridge relations and so on I think it is the best thing that can happen if it is regulated because you know if it's regulated it kind of leads to trust and if people trust this leads kind of to acceptance and if people accept it and they use it so it's a kind of an easy path for the trade-offs we talked a lot about them all these designs and all these things like anonymity and so it's they have their own benefits and they have their drawbacks so for open signs you know there is countries in the world right now in the 21st century where people are afraid to tell their opinion like what I do I openly say you what I think they can't so sometimes anonymity is good because then they can time stamp that they were the first who brought up their idea and they are not they don't have to be afraid that they will have some negative consequence because of saying this on the other side anonymity is sometimes criticized because you know if we kind of publish a scientific paper and somebody criticizes it maybe without reasons or with good reasons but it's done not in a polite way because of this anonymity it's sometimes also not good so it is everything has its benefits and its drawbacks and it depends on the context and that's what I kind of struggle with here guys is that we mix it up as Donke this was the best introduction we mix it up I told you in the ads of my talk open signs is quite big and I don't need a particular specific kind of use case we should talk about but it is completely different where what matters and for sure for every of the single questions I guess blockchain may or kind of the underlying technology DLT may provide some opportunities that we maybe could go for okay thanks I mean there are a lot of ways you can think of blockchain you can think about from a technology point of view which is kind of a decentralized ledger or decentralized state machine for a question but another way you can think about blockchain is from application point of view from the from the scientific society and also like in this community the way I would like to say blockchain is basically a way to create the decentralized trust it's basically this thing that creates trust among mutually untrusted parties in the old world you and I cannot trust each other and for example in the time stamping case you mentioned if we have like a notary service maybe you cannot even trust a notary service in the beginning if it's like a huge Nobel bonding discovery but with blockchain you can actually trust that this thing actually happened and with TCR the same thing that you can basically create this kind of decentralized trust among trust party so that is like a one-sentence definition I would give for blockchain to this community but do we have a trust problem like if I submit my paper to a publisher and it will like be received on this date we trust them right I mean there's no scientist that argues like putting it wrong times on my paper there are cases where people submitted their papers to conferences they appear every year they really liked the idea so much that they declined the paper and published it themselves so this is documented that really happened that's why we also have an extension for an open journal submission system so that when you submit your paper to a conference it's automatically time stamped I have to add Bella you're absolutely right and you know what why we need sometimes blockchain or this trustless trust in our community and the scientific community scientists per definition, per principles per our identity don't trust each other even me on my own if I don't know the authors if they are not coming from the institution I kind of am aware of if they are not publishing in a journal I trust, I read I don't even take a look at the paper and that might be bad that might be evil because maybe they have kind of something in it that is just true this would solve a lot of problems and the cases that Bella mentioned they are really so sad that they are true I think it's very true it's good that we are skeptical I mean just in the news a few days ago they found out that there was a bug in Bitcoin that would have made under some circumstances double spending possible I mean that's something we all agree of course that's not possible with Bitcoin but even in that system it was designed to achieve that it was possible and we can okay Lambert do you want to add something? Yeah, let me maybe introduce to give a little bit of another perspective on why we benefit from this trustlessness of a protocol let me introduce an example of blockchain in another but close field and that is higher education so since two years or so institutions worldwide who notarize allow people to notarize educational certificates so for instance diploma and so on on a blockchain and this is a huge imagine a country like Malta they even changed their legislation to support this and why do they do this as you maybe know for some weird reason I never get this why but for some reason it's hugely popular to travel to Malta and learn some language but what happens now is some school, some language school goes down the drain or take for instance Hungary they just outlawed one major university within their country for political reasons so there are lots of reasons but do not have this want to rely on the trust relationship to your alma mater on the long run but instead have a proof that you received some certificate on the blockchain and this is a well established case they even have standards governing this use case and so on and we can learn a lot from this imagine this kind of autonomy for learners applied to researchers that they literally own the transactions between them and there it's not about receiving a grade for your diploma but it's about other forms of assessment like for instance peer review this is super important or you submit an idea and you can collect likes for the idea for example or people retweet your idea and then we can like in blockchain world we could create new economies around that this is not possible in research gate because we know that research gate people can sit down in theory or springer nature people or LTV people and can change the likes with the admin password in the database this is super important because as a librarian I'm very much concerned about the economy of information markets and this has potentially a huge impact of how these markets work because if you imagine where like learners own their certificates where researchers own all kinds of transactions between them in a very literal sense not in this figurative meaning of oh we have some kind of peer to peer network no, literally they own this then you have these kinds of information potentially as a commons so people can build their business models for like delivering analysis of this data and so on upon this but there is no privileged access to this kind of information and this is a huge difference to what happens today day by day we rely on closed platforms we got used to it and these valuable branded platforms they have privileged access to certain types of information and they make use of it and we can bring hope at least so there is a decentralization we don't have a central third party anymore that can manipulate the data who owns the data they don't own it anymore but this brings problems as well if you don't have a centralized entity they can manipulate the data anymore then we don't have a centralized entity that can manipulate the data anymore and this is like the problem whoever has experienced running an internet service understands how hard it is to maintain the database in a state that is useful to the people you don't want to have 300 articles the same articles with different numbers or identities big companies like facebook there are a lot of mechanical turks working to cleaning up the database so that it's useful if you don't have this anymore we need to build game incentives structures around so that it's a good database and that's a tough problem for many things for bitcoin transaction it's easy in a way you really have to reestablish trust and reinvent some aspects of information markets and make it so that the people decentralize become creator of this data of this service we have projects that work on this and they understand that it's a tough problem so maybe decentralize services will be combined in the future or we will see like centralized services exist for low value transactions and for high value transactions like grant money distribution and things we might have a blockchain-ified thing is that a possible future? I think centralized services can still exist in the sense that it can be a major or main participant of some decentralized systems imagine we have this awesome journal that is newly established and the old school publishers can still be a participant in the TCR for example this is entirely possible I wanted to add some more skepticism to this whole decentralization idea for instance if you trust a well established institution for instance your bank and you lose your credit card or someone tempers with your credit card and buys something you can go and complain and get your money back if there is no such central institution for instance the big point equivalent is someone steals your private key your money is lost there's nothing you can do there's no one you can talk to there's another problem I don't think that decentralization can try to achieve but for some systems it makes sense for some systems it makes sense to decentralize trust for some systems it might not make much sense and I'm pretty sure that both concepts will still exist in the future decentralized and centralized system probably we have to make sure that the centralized data processing systems that they don't have full access to the data as well because privacy is becoming more and more of a concern because cryptography comes in so I myself don't really trust institutions or academia, academic institutions necessarily as well but I trust the math behind the things we are doing so I trust the cryptography that we are using and for instance I mean the bitcoin paper itself is not it might come from a well established institution but at least it's not labeled as if it was coming from a well established institution and look at Ethereum it's like an 18 year old guy who said oh maybe we can replace the scripting language and make this tour incomplete oh then he got money from Till Foundation boom there's Ethereum there's also not a well established institution so I mean yeah I think we will still need established institutions and central authorities to some extent but for important things and especially where it's feasible expensive we should aim for decentralization but I think the trust will change I want to give one example we know about these manipulations with car engines the diesel scandal and I don't think that something like this will happen again because nowadays I mean there were a lot of people that were involved technicians, people that wrote the code, people that it's a code, a lot of people knew about that but it could kept secret for several, several years but nowadays for example with the service I presented with your mobile phone even if you adjust the person that I don't know serves or changes the water bottles in the meeting room and if you hear okay this team here is discussing a possibility to manipulate this kind of data you could make a small voice note and say I was just in a meeting attending and they were discussing that they kind of manipulate the data from engines and if this would be documented in the blockchain then these big companies that were involved in this kind of fraud they would have to pay billions more in fines so I think by having this kind of transparency and the possibility to time stamp any kind of data people will have to be more honest or they will have to pay high fines in the future so first I want to say that in most parts I agree with Ismael and Bela so I think it's like in Star Wars if I stay with movies there is always a dark side there will be always people who will try to do something bad for money so I wouldn't go so far so to say that something like this would never happen maybe it will not take years that we will kind of get knowledge of it or maybe it will be in different settings so like never say never but what Ismael said I really like it and I would like to come back to the decentralization question by you Isamge so I think that we should go step by step here so I think what we will observe during the next years will be kind of such hybrid approaches we will have kind of central parties, big parties who still do the work and they of course get incentives for it but they will combine it with some decentralization that they will involve all other parties to participate they just need seconds to verify that the central party is acting according to the rules so there is somebody who has to provide computing and storage power there is somebody who has to do something and there is incentives like in Bitcoin and there will be kind of these hybrid approaches that they will open it up like in a blockchain that if they kind of compute the hash value they will do it because of course they will get something for it but it will take seconds for everybody who wants to see that they do it right and it's not only about hash value it's all about these processes and I think this is what will be the next step this combination so it's not like tomorrow there is only blockchains and there is no central parties anymore it will combination we will see some kind of central parties going down we will see some central parties going up who really better understand the new idea it's like with the internet some parties want, some parties love it's always winners and losers let me expand a little bit on that this is super interesting I think when we go further into the implications of making up these game like incentivation rules which are most often about and to regulate parts of real life through this made up games then we are quickly we have to be concerned about dark and potentially dangerous sites of these games as well so for instance there is a very well established notion in the economic research on comments that when you have some activity that so far is done out of an intrinsic motivation take for instance things like Wikipedia and when you introduce to such a system a monetary incentive you can easily destroy the system so think about what we do and this is not easy this is not an easy yes or no question but many of the systems we hear about today and tomorrow are about introducing monetary incentives to things like peer review and as you know so far this works just from the motivational standpoint more like Wikipedia you feel inclined to give back to your researchers your peers community by doing peer review so this is really something we have to keep in mind and this is why I'm grateful for people like Alexander von Humboldt Institute because they are doing this kind of qualitative research that we urgently need next to developing technical solutions about this kind of questions very good and I would like you to take the responsibility because you know there is libraries so we as society we as people pay taxes for society and this money on something society is crucial like doing research like educating people you have money to provide this computing and storage power to run these kind of databases without looking for other incentive mechanisms so if we as society decide that it's worse for us to have something like Wikipedia is great and it's also chronologically ordered you can see the whole chronology of all the articles libraries would run this and not compete with Starbucks for places where students can kind of drink coffee and learn but kind of do real crucial thing then this will be a great mover because we as scientists and students will for sure trust more the libraries that's your advantage than others so if we as society decide to fund such things make it possible you know I would yeah I think these are a great point but I would like to respectfully argue against the cautious thing you mentioned about like gamifying economic incentive and monitoring incentive I think having blockchain govern something called crypto-economics is actually extremely beneficial maybe we're still in the early stage but we're moving to the right direction the reason for that is what is crypto-economics is really economics plus code and that code actually dominates and you know explicitly how everyone how this economic mechanism is going to work and I think that is about 100 times better than what we have today which is a very ambiguous obscure way of governing the economic mechanisms yes there are a lot of challenges to make that explicit code work including governance including how to like you know there are people trying to acting as central bank these days you know to issue stable coins to have like a reserve and a bond system programmed as a smart contract but this mechanism I think could work and could work better than today because it is transparent basically talking about the society I would like the experts what's your opinion about how soon can we expect a technology based on blockchain so that elections local provincial or national level starts to become a little more real participatory democracy is there any hope for that anytime soon can you see that technologically speaking I would say the technology is far enough and I think also when we think about elections in Spain you know when they wanted to get independent if we think about how everything would have worked out differently if this technology would already be in the hands of the like normal person I mean what did the government do they send police forces to ensure that people couldn't go to these election rooms but if you were able to vote without going anywhere then maybe the whole outcome would have been differently so it really I think your question is a really good one because blockchain technology can have a huge impact on other society questions as well but let's stay with science and research we can like say vote on a good idea next good flying concept okay yeah yeah so it's opened up basically yeah yeah I'll have to go back to the election just for this one comment so it's actually happening already I just wanted to say that the mayor of Tsuk where our company is is super forward thinking and there were already possibilities for people because Switzerland is extremely democratic so to go and to vote on some local aspects actually taking this election example it's cool and it's like the blockchain and I completely agree to time same things but there's one big problem that is unsolved and that is in the science world the same problem that blockchain is not about replacing trusted third parties or like get them like get completely rid of them but we have to have new third parties for the real world blockchain interfaces and one of this is the identity problem so even the mayor of Tsuk has to have to find a way to prove the identity of somebody to participate in the election right so and we have this example and we talk about this right and then we have some problem of like how do we feed data into a blockchain if I totally immutable data set or whatever if you can't trust the sensor right we have a talk on this we have a talk on identity and we should focus on these discussions as well and then okay and then I want to like include one more thing into blockchain like all blockchain and this is new ways to look at data yeah it's like there are projects that deal with like today there's like this one thing and James said it like once in a good way like today we we give data we trust somebody with the data to do everything with it and just give them some data so we give some data very carefully in most of the case in research world right to somebody to do everything with it right so in the future we might end up in a point where we give all data to an entity they can only do something with it and very constrained things so think of sending all blood pressure data of all patients of Berlin it's my favorite example to a smart contract and that just and it's an internal review board IRB board can carefully review the smart contract and can see line by line that this smart contract is only able to release average blood pressure with a four weeks delay of all Berliners for example that would be a cool new way right I know I know that it's like at the moment it's not possible because the smart contract will leak the data to all every nodes that evaluates the smart contract but they are like publication and then we get into trusted hardware and everything but projects that work on this are calling their projects blockchain if fight data whatever because they have like how do we constrain the access to the data we don't want to have like one entity that is trusted with the constrainment we have several entities right and they call the system blockchain too to like so in this term like the blockchain of distributed trust becomes like the social, philosophical political representation of our responsibility to constrain the access to the data if we like come up with a thing that let's get all patient data from all patients and like send it somewhere we don't want to have just Max Planck server to trust that the data is constrained we want to have all research institutes maybe taking responsibility for that yeah so and this is like it has to do with crypto economies, strong cryptography new data handling ways distributed trust and this should be blockchain as well because we can like piggyback on the hype to introduce in these new decentralized data ways this actually is the most I think we will like in this next session we will talk about this yeah and have talks on that any comments about it or is it okay to call this still blockchain or is it too far out what would you say Ali Ali Ali you command on this yeah you are the computer you know trusted hardware you know that these are still dreams right how did you call what kind of blockchain and no no no not this is it has like this distributed trust strong cryptography a provable ability or auditability yeah all these things it has no blockchain I mean all the blockchain project in the future might not have a blockchain at the end as a data structure right so they can be something right but it's cool to call this blockchain as well if I'm careful like enough okay because it is distributed stuff strong cryptography and you command on the feasibility or later you have to go but I would love to see you like on the next session but okay yeah so one thing is how do you get the data into the blockchain projects they're working on this town crier for instance I think it's a group that's working on this but how do you actually make sure that the data you get inside into the smart contract make sure that it's actually the data you wanted to be in the smart contract yeah that's right but only the smart contract can decrypt it maybe you can just expose it to the outside and only how do you make sure the authenticity of the data that comes from outside of the block exactly that we have identity problem again right I could just create 10,000 of patients and just send it somewhere right so we have to constrain that as well and this is a big problem I agree here maybe a useful way to think about all this is to think about use cases where actually you want to solve like existing problems and you explore the problem space and then you think how could I use a blockchain or whatever technology that is there I think that's the right way to approach it in general yes and to expand a little bit on that maybe there are already interesting use cases out there that you can apply in research and science so for instance we had a super interesting hint to that cache and zero knowledge snarks and imagine that yes you can prove to your text office if necessary that you received a certain amount of money in a certain times man and at the same time to the rest of the world this is completely opaque and nobody understands this and this is exciting and think about this level of autonomy that you have above your own transactions and you can easily as an analogy you can find use cases for that or I see use cases for that and higher education and research as well yes it gives you much much more autonomy against like yeah enough said okay yeah so I just want to like do two things there's lunch outside and we continue and everybody who wants to go to lunch just goes to lunch the other people just stay okay is that okay and we open up the panel at the same time yeah okay so or should we just continue if you're hungry just eat okay just coming back to the data point a little bit like basically how do we see data in blockchain right so the great question is that okay we have all this cryptographic construction so we have homographic computation which means that you can do computation like entirely sorry yeah yeah yeah okay excellent yeah cool yeah it's okay yeah okay yeah yeah this is a very interesting topic yeah so basically like we have data on your head data and if we derive this from first principle that is like we want to use blockchain why? Blockchain is for decentralized trust to create a trust amount on trusted people so why do what kind of data you really want this kind of trusted services is your own data your own generated data your genomic data your browsing history your all that stuff so this is like for data on blockchain or data use case on blockchain is mostly about self sovereignty of the data right so you have genomic data you want to contribute to the scientific research but you don't want to like everyone know that maybe like I will go Alzheimer's like in 50 years so how do we do that the blockchain is a layer to break down the financial barriers to make the incentive work but there are a lot of things that need to be built on top to make this actually work and several key pieces including privacy computing that is like you can do computation on encrypted data and extract some information out of this and you know homographic encryption that is like basically zero knowledge proof that is you can prove something is valid and fit some property saying that okay my blood pressure is about 150 but like at the same time not revealing exactly what's your blood pressure for example this is kind of a thing that zero knowledge proof is and these things that would need to be built on top of this incentivized layer because at the end of the day you're selling your data you're selling yourself so this kind of incentive need to be realized on blockchain in a trust free way so yeah that's my I forgot this like the multi-party computation to like incentivize it that you have in a decentralized way yes that's right this was even the more obvious argument to call it also blockchain this new data handling paradigms so since nobody is going I have a question I'm over here it's totally okay that you just stand up okay I know what I mean like for lunch sorry I really like sitting I'm a little bit confused about this conference because I'm hearing I love that we're talking about blockchain and everything like that but it was my impression that was going to be how is blockchain going to help us in science with all the problems that we really really have and from what I'm hearing is that there's all this great technology but I'm not hearing a lot of how are you going to solve professors not getting tenure because there's so many people still not they're not leaving how are they going to solve the paywall problems how are we going to help people in countries in like Brazil they're not trusted their research is not trusted just because they're not at max Planck for example right so I'm just saying right you as a you have to move as a scientist to be these are the actual problems in science that we really want to solve so how is blockchain going to help us yeah good question we have like we create new incentive structures we create new different incentive structures we submit things blindly but immutably and you don't know whether it's from max Planck's idea or from like some remote country in wherever and some people don't accept this and you don't know whether it's valid it's from a arena it's from a well-known institute or not and you can reveal it later if you want and but people might still invest in it they might they might think it's maybe from Harvard but it's like really not from Harvard you know so they don't know so we have this pseudonymity that I could like think of right or we can have new day value flows we have new systems that can of course be game but the current system is game big times right but we just have like changing incentivization structures that we can easily build on top of blockchain systems because today we only have like one two three systems we have a monolithic incentivization structure we have like all these committees that like come up with review in processes because they have the obligation to the taxpayer to distribute the research money in a very well planned way right so it is this big effort of like grants and grant review and you plan your research for the next three years right like what we address today right but we have a blockchain system you can like rely on this obligation to have a trustworthy way of distributing the research money and in the same time have very innovative new ways so this would be one answer to this one vision now we are talking visions right it is like the phoenix from the ashes like blockchain was completely destroyed this morning now we rebuild it for the next one and a half days okay so just we are chiming on that a little bit also right so if we are talking about real problems maybe like the tenured problem that I also couldn't solve that is why I quit academia and started company so but another thing that you just reminded me is that it may make the flow of public contribution to research funding much more easier so let me just give an example here so in Berkeley there is a project called bonnick and bonnick is about finding aliens so it basically analyzes the telescope data and try to see if there is like a planet that is suitable for human living and maybe aliens like little green guys are living there so that project is struggling right so they cannot get enough funding because you know who cares the finding aliens right so but if you think and there are a lot of projects like that so basically you can install a software on your laptop and fold proteins for medical researchers but no one is doing that these days now but what blockchain can enable is this kind of frictionless payment friction is micro contribution to researchers right so you could now actually start to run a folding protein program on your cell phone or on your laptop even when you're sitting at the conference and at the same time someone some rich guy or some like a research institution who has money can directly fund this process by giving your cryptocurrency because the cryptocurrency so entire friction to cross financial barriers and financial silos are so low that it's not becoming a problem if you're just doing like one dollar of work you can do one dollar of work and still get paid but you just couldn't do it today because of the financial barriers and that's kind of the thing that's just one thing that can you know immediately make me think of how this can help research we have to close the panel lunch so can I have your gum actually one two three hello if you need to eat the restaurant is to the left and to the left again thank you one two three four five six seven eight ten no one in Russian still doesn't understand I'm not good to see good afternoon good afternoon I'm James Little John so hello to all those that don't know me and I look forward to meeting those that I don't know already during the rest of the event I'm going to guide you through the data segment this afternoon and I just want to introduce this by taking up a point that John Tennant made about if we had all the things we agreed on all the things we disagreed upon and if we did that exercise my hypothesis would be that data would be the place that we could maybe achieve consensus and that would be the goal for this week he also mentioned that he would like to see more librarians in the community so I don't know if you can read my t-shirt but in the start of the year and our first speaker is part of a project called Damahub Dennis and it's top heavy with librarians in the caveat it is a small community so with that I'm going to pass you over to Dennis to talk about the Damahub project thank you and introduction from lunch how many of you guys know what Zhenki has been doing for living before he decided to dedicate his life to make science more open so you know Zhenki is a doctor but what kind of doctor is he and what he's been doing for a long time I'll show you a short video in 2 minutes sound on please hold on it's volume off where these arteries are what these arteries should look like and where there should be blood flow and when there's interruption in that blood flow it sends off an alert so the goal now is to get the clot out of the brain as quickly as we can if we cannot get this clot out of the brain the whole area of brain that you see here in green the whole area will be dead most likely so what we did in this case is use a smaller bore catheter to grab the clot this is actually the culprit for all his symptoms and now we have it outside the body and we have full restoration of flow hello how are you doing there sir good to see you so Zürnke is a radiologist 15 years ago I was brought into the Irish hospital with severe headache and the following day Zürnke's colleague Dr. Brennan stuck a wire into my leg brought it up to my brain and sprayed in each of four arteries contrast taking pictures this contrast filling up blood vessels in my brain then he called neurosurgeon named Mr. Ravlik and they looked at the pictures and they declared two things first they said there is not much brain the Irish and second they said that what there is a mess couple of hours later I had to bring back to the radiology room for another angiogram and shortly later I was given two options I had to decide the following morning whether they should do they should perform open brain surgery on me or they should try to fix to fill up the space which was created by bursted aneurysm through my leg with a coil and like in the situation like this you really want to make the best informed decision as possible but I was bound to the bed and the internet was still the mobile internet was still quite poor then so I asked three of my friends to do as much research as they can and all of them all three of them came back with the first thing they said that they hit the paywall so I am here to I am very grateful to to Yankee's colleague to introduce me to the problem of access to information and second I think we should all be very grateful to Yankee for organizing this event so I think he deserves another round of applause I was very lucky to be born in Soviet Union as a look back where all school books were free education was free and medical care was free but what I am trying to say here is that I do not remember the moment when I consciously decided when, where and by whom I was going to be conceived and that's I think true to anybody here we don't choose our gender our skin color we don't choose how prosperous our parents are so I think that like and I have Soviet idealistic views that each life should be equally valuable and I believe that anybody anywhere in the world should have access to vital information when it's needed like researchers, patients, doctors we live in the world which is driven by algorithms today so for example in China there is a social scoring system on trial at this particular moment and that system allows Chinese government to combine academic records with medical records, with criminal records with social media records with financial transaction records with shopping habits and to assign to each and every citizen a score so if you are buying a pack of napis you are carrying parent and your mortgage like the interest you are paying on your mortgage should go lower if you are buying a pack if you are buying a pack of beer you should expect that your health insurance premium could go up and if you are disagreeing with your government it's very possible that you won't be able to buy a train ticket and if you are on the train you should expect that to hear announcement that if you don't have a valid ticket or if you have if you misbehave yourself you should be recorded on individual credit information system this picture was taken a couple of weeks ago by one of my twitter buddies on Shanghai Benjib train so it's all reality today and if you think that any kind of legislation or your government will protect you from this kind of algorithms your dream and your not real because algorithms have no borders and companies which provide governments with algorithms they are at that moment refocusing from making money from utilizing consumer data to providing and selling information to your government to your bank and to insurance company so on one hand it can be used to help people to make to help patients and doctors to make life saving decisions on the other hand it's just a tool that can be used against us and when it comes to research data publicly funded how is it stored well it now now lives on over repositories around the world and then it advertised in one out of 30,000 academic journals and as we've learned from John Tennant early on in the morning only 25% of them are open access like this map approximate of institutional repositories they all of them have at least things in common first like institutions which built them invested lots of money resources to to help them secondly like it takes at least to people and $300,000 at the very minimum to run each of them and each each institutional repository has a single point of is a single point of failure and I believe that we should move from infrastructure for preservation of research outcomes of with science do not turn off into the system which cannot be turned off and how the system should look like I'd like to compare it with the road network the first sophisticated road network was built by the Romans during the Roman Empire times and they didn't ban the roads obviously but they were the first to decide that the roads have to be as straight as possible and the roads basically helped the empire to exist for 500 years and it became roads became arteries connecting the vast network of the melting pot of cultures, religions and institutions they served the purpose they allowed to move troops from Portugal to Constantinople as quickly as possible goods delivered people were moving so many of us here I believe want to build applications some kind which will improve or which will make the science more open I see applications as vehicles which go on the road and each piece of gravel on each stone which goes into the road can be seen as a research object but before we are building this vehicle which will be using the road I think we should have some kind of idea in what kind of condition this vehicle will be used will it be used because unless we know for what kind of environment the vehicle is built we may end up driving tractors Belarus on German autobahn and drive from Barginis on Russian Siberian roads there is nothing wrong with tractors Belarus I have to say they are probably the most unhackable tractors which still remain let's stick with Lambos how many of you want to build killer apps yeah you? no no we don't need killer apps we need Lambo apps and but Lambo apps I mean applications which Lambert Heller he left he has just left Lambert Heller and his colleagues academic librarians can advise their researchers to use when they come and ask him what they should do to comply with increasing demands from funders from European Union to comply with data preservation policies and to make their research outcome findable, discoverable and reusable for generations to come yes, actually Rachel Lamborghini like when he started from building tractors and then he moved to supercars but like if and Lambers which I built now they still able to pass each other on the road because when they build their road network decided that each road needs to be at least 4.2 meters wide and we're still building around the world roads which are as wide as this and if you look at the cross section of each road we create a compartment and you fill up with gravel and different sources of material put on top and then it's maintained and lasts for many years so in the same way we should see digital infrastructure for preservation of scientific data and vehicles which will be on top of it and they will be using it so there is a couple of people here in the audience James and Karman was participating in our events and Zhonky's we've been thinking for what cross section of infrastructure for preservation of scientific data should look like and it all starts from from protocols we need to decide what works and needs to be preserved so we need to know what is like what kind of what is data object and what kind of metadata we want to be preserved we want to use peer to peer open the license protocol which allow to address each and every research object based content there is a number of groups working in this space at this moment IPFS has been mentioned already which is interplanetary file sharing system SafeMate is working on develop something similar or that project for example and we know for sure that the system which is works to be created needs to be decentralized because otherwise we come back to the system which has a single point of failure which can be switched off intentional or not and we need to reuse what's already useful such as digital object identifier or cheat ID services go on top of it and applications so yeah let's reiterate on it there is a number of groups now deciding what research object is we need more academic librarians like Lambert to be included in the conversations like we are having here distributed like openly licensed hypermedia protocols which allow to address those digital object by their content IPFS needs to be like we see it as a solution for creating this distributed system and it has to be governed so in the way that we can audit and verify on what kind of system and surely you need to find stuff so like those objects need to be made discoverable so I'm inviting you here to help us to develop and to participate in designing the system which like to design governance is very important because people who are using the system have to have a stake in it and they have to be able to influence decisions which will affect it so if we want to use if we want to use if we want algorithms to benefit not only governments corporations and banks but them to be employed to help researchers doctors and patients to make important decisions we need to create a distributed system which allows us to to make this data findable, accessible, interoperable and usable yeah so there is a number of groups trying to resolve it to look at it on different levels there is for example Freya project which is funded by the European Union it's three years long there is like a protocol labs working on IPFS which created IPFS and they're trying to resolve the problem with like those identifiers needs to be persistent and immutable which is still an unresolved problem European Union has the European Open Science Cloud which needs to be included into conversation and then it's intercontinental because in Europe for example there is a research data alliance very active in this space and in the United States there is data together and I don't think that both talking to each other so all of them have to be included in conversation somehow before in order for us to create this infrastructure where we can drive Lambos thank you Dennis so we're now open for questions if you put your hand up Mike will come to you I'll just maybe ask quick one Dennis you do a weekly discussion forum and you've done events to find out about where you meet up yeah we have a weekly call every Tuesday at one o'clock you can find information on Gitter or about it and yeah choose the call it will be the best way to contact you can contact us individually and we'll put you we'll let you know what's going on okay thank you very much so we're just going to take a small break because all we all know is data scientists we don't collect data we can't do the data science Alexandra is going to make a plea for some data from you hi just a quick announcement so my name is Alexandra I'm from the blockchain and society lab at the University of Amsterdam and together with and other researchers at the Netherlands we're doing a survey that maps projects that are involved in the blockchain for science community what are the challenges what are the limitations and the potential we have an online survey that we would all like for you to participate I can also do a quick interview with you later in the day or tomorrow so please come find me whenever you have time it'll take maybe 10 minutes thank you and one other omission there was meant to be a poster session during lunch but due to running late all those great conversations over lunch we'll do it tomorrow so our next speaker is Conrad someone that's new to me but this internet is a great thing so I did a stalk on him and I think he's at the co-face of data science he's got his public keys on his website and all his data well organized so I'm looking forward to hearing more about what he's doing okay thanks I would like to talk a little bit about how we can hopefully generate open knowledge based on closed data and what kind of new deals are out there to make this happen smallest claim in this perspective or in this regards is I will mention some companies later on that seem to have solutions regarding this I have no connections here and I'm coming more from the perspective of the bioinformatician who crunches a lot of data on a daily basis and enjoys doing this in the open so as an open science enthusiast and John mentioned this already in the morning and he actually laid the foundation for this talk in a way in science everything data source code and clearly in the end the paper has to be open and the others would not be good scientific practice I like to avoid the word open science often because as John also already said this is just pure science that the foundations of our scientific process is openness and there's a small but whenever I give this workshops regarding open science and how we can implement this somebody raises the hand and says but well I have a computer that is linked to personalities that is linked to patients so there is a higher good sometimes which is called privacy if I'm a patient I have cancer I would like maybe to donate my genome data for example for research purposes but what I do not want is that this is somehow linked to myself and in principle this is only one we have a lot of data that we should share but maybe should not share because it has an implication on how we can live so behavior data everybody or many people have fitness trackers for example that track behavior or what am I eating all these kind of things can be stored and can be used in science to see general trends socio-economical status is also something that in principle is can be a piece of research so you can collect this data and try to make scientific statements out of that but as an individual I to be honest would not like to have this in the hands of other people medical records we just saw the example before by Dennis that you basically sharing this data can be useful for the research process for researchers but for the individual this might be not so beneficial at least in a certain amount of time and if we come to the core of ourselves the genomes or axons or at least some snips and these are maybe some biological expressions but I think everybody is aware that we carry basically the blueprint of our body in us and every cell so the genome the DNA is an important description of who we are and well how we develop and how we live today we have actually technologies making this easily accessible this is one chart that you find very often the first human genome costed around 2.7 billion US dollars and took 10 years and this was then available roughly the draft in 2001 and when you then started to sequence a new genome it just costed 100 million cheap in comparison today and this is due to different technologies that arise roughly in the mid-2000s today I can sequence a genome in roughly one or two days for around $1000 this is definitely a game changer and I'm pretty sure many people are interested in having access to this data for their own purposes for medical reasons for example in order to have personalized medicine and this is a very powerful tool that will definitely change how we can do medicine and how we can do science and then we are not only our body here but we are actually an ecosystem and we're carrying a lot of bacteria in us so the so called microbiome our gut microbiome, skin microbiome all of this can be tracked today again sequencing technologies are actually helping here and also this is saying something about me and also this can be something very interesting for researchers and then anyone would like to even connect all this so if you know how people behave or if you have certain traits how they are linked to the genome this is then the interesting question that for example G-Bus analysis can solve so in principle as a researcher with a lot of interest in this type of data as an individual I am actually not very interested in sharing this because this gives a lot of weak points maybe to others so scientifically speaking we have a lot of interest having these data of a large population and it will dramatically impact how we can science, how we can do research to do that but on the other hand this can be really a problem if this kind of information leaks and is accessible because this can lead to systematic discrimination due to political, ideological or even commercial interest maybe the health insurance is not taking my contract or I cannot sign a contract because they know I have a certain disease and I have to pay more for that to take another one and this is kind of questioning our solidarity system maybe at some point people are discriminated because they carry a certain allele of a gene so in principle there are good reasons to make this data open but there are also a bunch of good reasons to not make them open so we have clearly a moral dilemma here should we protect our rights or should we push the scientific progress and this was mainly for medical data but clearly this kind of situation is also in many other fields for example financial data of organizations you could do really make interesting research on top of that but the individual organization like a company might not be interested in sharing this energy consumption of devices for example it would be also engineer devices differently location data of vehicles all these kind of data from different domains have a similar problem they might be very interesting if we have a large population where we can have access to but it brings issues for the individual there or the organization so how can this be solved so is there kind of the possibility that we can generate an open, ideally open knowledge on close data can we have kind of black boxes that we can maybe see the full data but that we can at least reproduce if somebody claims something that we can go back to the same blocked or hidden data run our algorithm and get the same results can we maybe train machine learning models on top of that data and use that for analysis later on or at least can we make predictions on top of this close data that then can be confirmed in different ways so using this more as a hypothesis generation machinery how is this done currently just an example Genomics England is a state-holder company that aims to have 100,000 full human genomes which is huge what they do currently they have close data centers where only certain people have access to remotely and they can run their algorithms there and only the results leave this via an airlock similar approach is the so-called personal health train they have these data stations similar to this so basic data centers where you can push in some algorithms some more programs actually and you get some data out so again both of them have locked systems and you need again as always you need to trust these instances and trust is something that is not always well-earned for example 23andMe a company that brings genome information SNP sequencing or SNP information to the broad population and then they sell it so you went there you just want to know a little bit about your own background and suddenly they sell information to others once again this is nothing you can change if you lose your key, okay if you lose your bitcoins, okay this is your damn genome you cannot just get it back well there's genome editing but this is something far away and this is by the way not only your genome this tells a lot about your family as well so this has huge implications and this is really a catastrophe so there must be better solutions and there are so I said with this question in mind I looked around a little bit and tried to understand where we stand in respect to that and there are blockchain based decentralized data market places that try to exactly help here the promise is that the data owners so for example if I sequence my genome I can put it somewhere and try a full control about what of that is shared and with whom that is shared one important thing is also kind of a standardization of data and what the let's say the people who want to consume the data have is kind of that they can incentivize to get more of their data and there it becomes already a little bit critical but in principle a genome costs $1,000 this is still too much for many people but if you put into such a system into such a marketplace information about yourself maybe you have a certain disease maybe you're healthy I don't know but if you put this information into that marketplace the data consumers can contact you indirectly and tell you okay if we get your genome you will get this and this token that can be later on be traded but with this they can have an incentive or given incentive to sequence certain people or to get more information doesn't have to be the genome sequence can be also other stuff but with this the idea is actually to promote this accumulation or this collection of data in a standardized way in an anonymous way and give also the power to the data owner again and this to be honest sounds very interesting for pharmaceutical industry this is very interesting because they can have this traceability again if they say okay we have a bunch of patients here we do this and this try on them and we get now this wonderful results and we can sell our medicine here but under the hood nobody can prove this with such a system they can always say okay here's the data if you run your own analysis on top of this you should get the same results and this would look then very simply like this you have the marketplace the data owner give access to the data to a data consumer and return get a token very simply speaking and still keep as said all the rights all the power over above their own data there are certain underlying concepts some of them were mentioned before fully homophobic encryption in there and as far as I understand doesn't was not really well implemented so far multi-party computation might be a solution basically you break down the problem into smaller pieces and an attacker would have to have control over the whole network they built on certain hardware concepts trusted execution environments like SGX from Intel there are a lot of these things out there at least as white papers discussing this and said this would look very roughly then that the data consumer ask for example for certain data might find it already in via the blockchain sorry the data consumer might ask for this might find somebody who offers this already or motivates data owners to contribute their data the data importantly is stored off-chain so is outside there and is not stored in the blockchain and then you have these secure compute nodes SGX for example and the data owner allows the data consumer to have access to the data to give it basically into the secure compute node and only gets in the end the results of that computation so rather elegant but also rather complicated system in my opinion and there are numerous protocols, providers that have kind of a general purpose solution for this at hand, ocean protocol we will hear right after me I guess, enigma protocol they have the concept of secret contracts basically smart contracts but in these kind of encrypted environments or in these trusted environments the key in protocol from the ASIS lab and open mind clearly with a focus on machine learning although I think the ocean protocol also has a focus on this so there are different potential providers of solutions in this perspective and they are not limited to a certain use case but are rather broad on the other hand we also have kind of more specialized providers coming from healthcare and they come with these kind of concepts so very elaborate it is already Nebula and Long Genesis so Nebula has to please keep in mind this is done by George Church who is a big driver in this genomic field and strong person in that field there is also Lunar DNA I am not sure how to pronounce this PHAROS encryption and all of them offer solutions basically that you are not unfortunately not yet offer solutions but they tell that they will offer solutions where you can either give health data, health records or even genomic data and Nebula is even working together with a sequencing facility in order to generate the data to store the data and then put this into these private pots that can then be managed via a blockchain approach so there are already a lot of people in the boat who offer solutions that sound at least interesting to me but now the question is will these data market places really improve our science but I would say maybe and this has definitely potential and I said as a bioinformatician this is kind of the paradise for me if we have access to this kind of data this would be really great and I think it's a trade-off between openness and I said I am a very strong open science proponent and I still always have these debates and they could be stopped here because we can say here is a mode where we pay have kind of a trade-off we pay off a little leave a little bit of openness away but instead we have access to lots of data and this will push our knowledge dramatically in my opinion but currently maybe I'm wrong and I'm very happy if somebody can correct me here I see only a lot of white papers and for this I could not test anything here maybe I'm wrong and maybe somebody can do a small demo later I'm very happy to see that I completely agree that this should not be out too early in this case once again this is basically your genome and unfortunately the discussion is happening mostly by companies and not academics so thank you Zunke for organizing this because here is a strong proportion at least from the academic field and this is important I see a lot of potential here and it would be a pity if this is ending up in the protocols and proprietary solutions and we are out of that again and I mentioned this before it's good that it's not too early out there in my opinion because once your genome or at least snips of that are out there you will not get that back so this is really crucial that we have a rock solid solution as I said with bitcoin in the worst case yes you lose maybe a large fraction of your money but your genome you will never can replace and if you have a disease and for whatever reason somebody makes this accessible and this will be out there forever and also for example your children or your family so this can go back in your tree of life in a way and there are also other issues that even if you have not direct access to the data we can still use certain tools to well de-analyze the data there is a paper from 2013 where they used certain traits and could link this again to last names this is again a crucial thing and it's too precious and I made this rather simple with my little drawing how this should work but the complexity of these systems is dramatic as I said this is a multi player solution you have a lot of things to keep in mind here and it's very complex and this means it might break easily you might also have problems with different legal systems again we had this I think several times before it's clearly it's a global thing and nobody can forbid me to put data there but maybe in the end I have some issues if I want to use the data and what might be also an issue is that we incentivize now people to contribute their genome but they are actually not aware of these problems that they say ok this is good quick money for myself I put my genome I put my behavioral data in there and then they afterwards recognize that this is a problem that they cannot get that back so education is needed as crucial as always thanks John again education is key and data is as said stored off chain and this is kind of my opinion outsourcing the problem to others and this has to be solved I read in one white paper for example they suggest to put the genome then on Dropbox that's ridiculous this is the most precious thing who would do that I wouldn't at least no well and who makes sure that the claims that people write for example put into the blockchain order to be found by companies incentivizing them that they are not wrong if I'm a poor person I have depth and I know that if I'm belonging to a certain group my genome is sequenced and I can give this and get money for that maybe I lie when I fill out these forms so this is my opinion not clearly solved bottom line this is super promising as a bioinformatician this is awesome having this access to data and as a trade off between openness and privacy but I think there's still a long way to go but we should go it we should try to get it and see if this works out for us so what are your questions thank you very much yes please thanks for this presentation you mentioned this in the companies like from George church and so on I'm a bit critical about this I wonder how much this is not creating just new silos because they are actually to my understanding all ICO driven projects that just were there when you could still make money with this last year they were quick and George church is always quick doesn't mean that he always has the idea by himself because origins then might prove that many of the ideas others had before but he's very loud that said okay now it's there but I think just it creates new silos and I don't think actually in the interest of the this movement that we are trying to I completely agree with you and this is why I also suggested we academics have to have the discussion because it's already ongoing there and we have the risk that we are outside of this and that this is just a big playground for pharmaceutical companies and not for the general public anyone else no we'll keep the good time thank you thank you very much a year ago I sat down with Dimi in a white board and some because I was watching I think asking what language we were speaking so that was a year ago and I think from that the ocean protocol emerged in some shape or form so I'm looking forward to hearing where it is and where it's going over to you Dimi Dimi, sorry fantastic hi everyone my name is Dimi I'm from ocean protocol I've been working around decentralized data for a few years now and we started up with looking at intellectual property and creator rights in a scribe now we moved on to how can we create open source decentralized databases like big chain DB and it came down to something that's now ocean protocol where we're looking more at intelligence data without humans without consolidation is not much worth so we're looking into public intelligence networks incentive systems around those and it's early days for many of these things but the paradigm shifts that we're employing are interesting and promising and at least it's something else I have a background in machine learning for let's say micro electronics modeling and I used a lot of predictive models to check what's the actual performance of such designs of micro electronics into the real world and some of these things would take like years to compute taking into account all these process variations and stuff so we would make models out of them, accelerate and we always were looking for a better model but rather just looking at more data would have given us the same results without basically being skeptical about is it a support vector machine a neural net, some Bayesian network so it's shown that if you just feed more and more data to AI it becomes quite powerful and this data revolution has been starting for 15 years and there's a few entities in the world that are really good at it so they get most of the benefits just to give you an idea we're working around something called autonomous driving there's this mobi platform tries to pull a lot of car manufacturers fleet managers you could say anyone with a dash cam and it's all about looking at what's the amount of data required to create models that are safe enough to employ into autonomous cars and it turns out that it's about 5 billion miles maybe more and that would take maybe 40 to 50 years to acquire for a single company so pooling between companies might be interesting so data pooling by itself is very interesting but then also opening it up for an intelligence network of data scientists is even better so we come to a point where we see that there is a lot of data out there but it's locked up and only few enterprises have also the data scientists to consolidate that data to extract the value from it there's a lot of AI startups typically coming from big companies but then they don't have the access to the data so in the middle there's just a few lucky few which obviously sometimes crew it up or they well you could say don't be evil it's something from the past already and yeah data is a lot of value and a lot of money and it leaks and it breaches and yeah we kind of got used to all these things but I think giving a more equitable model for this is more sustainable for the future so that's what we try to implement in the protocol because well it's an open source community it's not really an enterprise we're not out there to create money we're out there to make something that's sustainable something that well can give you an alternative to existing data monopolies or AI monopolies and it's all about democratizing access to data and AI or intelligence some core principles are self sovereignty being the owner, the controller of your data assets also attribution and provenance and of course privacy so trying to disintermediate between these two worlds doesn't only need something like monetization in the middle but also something about the commons and commons is something we tend to forget that it still exists however if we're working open source or in open data or in open science then you could say the commons is the open source code maybe that review everything related to digital commons and media art but it's something that companies don't really tend to implement sometimes they create an open source project in a service layer on top of that and that's quite nice I think that's an incentivized commons that's basically one of the things we like to think about so rather than siloing resources into centralized economies we're looking at pooling resources decentralized in communities and so one of the first things we did one and a half year ago was creating like a data sharing tool it was about data access sharing and this was a project together with Toyota and well it was more exploratory looking at how can you open up or connect multiple data providers without actually leaking their data so one of the big problems is that companies want to share data but they don't want to have their data escape so as in the previous talk was mentioned is that is possible and you can use technologies like multi-party computation or homomorphic encryption or trusted hardware but still you're relying on a lot of components and I think if you look at data sharing it's not the sharing that you want it's the consolidation of the data so typically you're looking at how can I prove that I run somebody's algorithm in my data center and how can I prove that I actually did it and that I actually run the algorithm on the correct data and can I also deliver a cryptographic proof or some form of trust that vouches for my actions so many of these things were encapsulated in this project and that's kind of the start of Ocean Protocol we're working with a company in Munich who's called Connected Life and their privacy is of course well it's health data it's health monitoring data and there is very important to look at how can we preserve privacy and negotiate privacy and how can we make sure that there is no leakage of the personal identifiable information sorry I'm having some problems with my... yeah, yeah, I don't know how it happened cool, alright give me a second okay so Connected Life is a company in Munich they're looking into DNA and other types of things mainly related to Parkinson and all the data they can gather is useful but they don't need to know the source of the human they just need to know the data around the data so that they can have data scientists exercise their algorithms make better predictors and automate the process so looking at these things then I think things like well you could say a fund for data science maybe getting a hard time on my press maybe well just looking into another use case here we have something called the universal recommender and think about all the data that you use for labeling what you like, what you don't like the suggestions you get from Netflix, LinkedIn all that personal preference and opinion is now somewhere scattered if you would only have like one minute of your digital life on a daily basis what could you have for an AI assistant and saying like what would be the most interesting thing for you to do now what would be your most preference action or best service to connect with so can you gather all these personal preferences into your own digital software and look at my personal universal recommender could be trained on humanity but could be personalized towards yourself think of it as a form of AI assistant or coach learning of all the actions you do but staying on your control on your software access so all of these things are quite promising but then why would you use a blockchain to help here I mean it's about self sovereignty it's about privacy preserving tools a blockchain is just something that connects these things and I have like I think I have three versions of a blockchain that explain what are the aspects that we think are interesting to include in this data sharing economy so first of all a blockchain as a chain of blocks which is all about provenance and provenance of things that happened in the real world claims, proofs and they have consensus power this means like the proof of work that a blockchain does or proof of stake of other blockchains and sometimes I could just compare it a bit like carbon dating it's basically a forensic tool that allows you in the digital age to say that well somebody made this claim at this point in time and it's being agreed upon by a majority of consensus so in notion protocol our applications are data service supply chains they're basically a combination between data algorithms and compute and this means that an algorithm can run on data in some suit environment and then store the result for inspection or maybe for annotation and what we want to do is well we create time stamping processes in the middle that actually say that well this person actually delivered data this entity delivered algorithm and this compute did its job they combined the data and the algorithm to store the results somewhere else and all these actions get recorded as a provenance tree on to a blockchain so we're not only looking at single providers but for each of them like a full network that you can say well it's an inter-service network it can combine any type of service for data or algorithms or compute into a full network so you could always choose what's your what's the cheapest what's the most decentralized what's the most privacy preserving best encrypted what have you another way to look at a blockchain is a world computer and there we have smart contracts running as kind of unstoppable codes on to a world computer and for us it's about creating agreements and agreements around computation is well where does actual computation is going to take place is it on my site am I going to download the data or am I going to send out my algorithm towards a trusted provider towards the data owner and we have to have this negotiation and that negotiation goes into the conditions of a smart service agreement or just let's say a smart contract containing a service agreement so this is quite interesting because it gives you a bit of mutual protection between sites if you're a data consumer and you say well I'm only going to pay if you actually show good behavior on let's say good behavior is running my algorithm on to your data set whilst the data owners could also say well here's a little bit of warranty that if I behave badly you get basically part of my stake in the game so here you can play with negotiations and agreements between parties and I guess if we're flexible here we can encompass a whole range of use cases not only look at privacy preserving but also public data now data science is a bit of tricky what we have is that we have to combine at least three ingredients to get intelligence data and then human work in an algorithm and a compute layer now obviously not every configuration is perfect so private data doesn't want to leave no data escape but big data also doesn't really want to leave because it's just too big you can't push it over a wire sometimes there's this thing called the FedEx bandwidth and basically says at some point if the data becomes too big it's more cheap to take out the hard drives moving the FedEx truck across the country than sending the data over the wires so assuming that big data doesn't want to move the algorithm to the data side and that's something you'll see in a lot of hardware manufacturing processes as well NVIDIA is optimizing to put more compute facilities around the data storage site etc so this is your negotiation patterns that you have for as a service agreement well it's a smart contract has three parts the service that you can detect on a metadata store then you have conditions which is cryptographic challenges that need to be solved and then you have a reward section for payouts and the payout is according to the service quality that's being validated so each actor in the system might have its own conditions to bring to the agreement and its own terms of payment so creating a flexible platform for the ocean contracts that we're providing and many of these conditions aren't ideally they're cryptographically secure but sometimes they're more subjective and then you have to have stuff like human creation, dispute resolution albeit legal or not one of the use cases we have and we created an infrastructure around that is where there is a secure sandbox at the data providers side the data always remains within the data provider and then data scientists can submit algorithms to this data science sandbox and that data science sandbox generates proofs that it actually run this algorithm on a data set and those proofs are the ones that go into the ocean network and access control for allowing the algorithm to go into the data into the sandbox is what's happening in the service agreement we're creating a few interfaces for data discovery but also how you would use ocean in a Jupiter notebook we just want data scientists to use their own tools we just have this additional superpower and that means we'll connect to more data sources discover monetize data what have you one of the things we're looking for that we've also been working for a lot is how can we signal relevance of data sets and there is this interesting concept of creation or tokenized creation that allows people to basically lock up some portion of money saying that well I think this data set will perform well in the future it will become popular so I'm putting up a bet on this data sets popularity and if it gets used more I get a bit of interest from that bet the last version of a blockchain is an incentive machine where we're looking at how can we have a blockchain that rewards people with minting or creating new tokens and assigning them to people with good behavior one of the earliest examples is for example looking at the bitcoin network here people have been adding compute power to the network hashing power because they got rewards for it they got bitcoins and what you get now is this huge supercomputer that basically has A6 custom chips has people operating them in mining farms and there's a lot of people acting around this network just to get that bitcoin reward so you could say this is a quite effective incentive machine now it's also a bit of a dangerous incentive machine because it only has one incentive that is add more computers to the network secure the network more and more and then you can create something like well here's a paperclip optimizer showing that maybe we should be more careful in designing these optimization functions or these objective functions so what would it be for open data, open science I think there's a lot of debate that you can do about incentives for open and common science what would be good incentives, what would be bad incentives I don't think a single objective function would fit but looking at the core values of this network where there is self sovereignty there is attribution there is privacy incentivizing maybe relevance and quality openness so everything that can be kind of proven or at least vouch for in the real world can become a lottery ticket to a reward function that's an interesting mechanism because then you can earn tokens by having good behavior and use those tokens to consume more services or get a bit more governance or control in the network so if I look at behavior in myself I have like like most humans we have two actors in our brains one of them is a rational decision maker the secondary brain part and then we have this primary monkey in our brain which is all about instant gratification and those two have to be taken into account when creating an incentive system now for ocean we have something called network rewards it's basically a big portion of the ocean tokens are locked up at least across the operations of the network towards what we think is good behavior in the system of course what is good behavior is subjective and it's governance now for us our initial design function is we want to maximize the supply of relevant data services data services, data access storage algorithms, compute creation it's all part of that so if you can prove that you delivered one of those services in the network you get a lottery ticket and every 10 minutes or every hour you get the chances that you get drawn from this lottery and you get tokens as a reward this means that governance becomes more and more important because it's about how you steer the network function the objective function in the network and how we're thinking about this is well there will be a form of global network governance talking about protocol updates but if you have then specific let's say data pockets or knowledge tribes then they have different missions and visions they might also have different types of incentives, tasks bounties and things to be solved so grouping these things into more clustered tribal systems we call them but it's basically communities is part of our design as a last slide I just want to think about a few things that might be interesting for discussion so for science and research I think provenance creating trusted knowledge graphs, curated knowledge graphs maybe think about if you create a dynamic paper in the site and if you click on an experiment you can automatically see the data flow from previous experiments until the source public funding and rewards currently it's institutionalized but I think many people would benefit from a kind of more open funding system governance around research projects publications what gets accepted into what not communities but also just signaling of emerging properties and locking up a commitment saying that if this gets accepted as a project it's actually going to release my signaled funds hence promoting more and more emergent problems and things that people care about and not only like institutions or governments so feel free to have a chat with me maybe you can flesh out one of these things yeah that's it there's also well there's a lot of if you want to know more about ocean there's a lot of things you can do to help or to just check out some of the code we're doing we also have a big bounty system we already completed a few interesting ones but you can also just suggest a bounty saying that well this would be cool to do with ocean protocol can you guys let us with some tokens or everything related to the bounty infrastructure that we're using so that's me if you have questions go ahead so Conrad promised us it would be a complex world but thank you very much for a well thought out explanation of the inside workings I think I've seen a hand up at the back thank you very much for this idea and how far are we away from playing around with this so I mentioned before that I couldn't find really something that was so really useful where we actually could put something in practice how far you're away from this so let's assume I have a small use case an academic small use case I want to run that can we do this tomorrow or do we need to wait where are we standing here I think you can do a lot today we have a thing called fit chain which has the on-prem compute with containers so you basically what you do is you put your algorithm in a container you ship to an on-prem compute and those two services are enabled in two weeks we'll release our second version of the test network so you also have like you don't have to care about running Ethereum instances or nothing like that just and then you can plug in some of the Jupyter notebooks have a few modules around that as well yeah I mean just check the GitHub there is a lot of things popping up every day so that's cool thank you thank you how do you go about preventing like the rich multinational organizations or enterprises dominating the open source systems yeah that's a good question if you create decentralized systems and then you have a few whales entering and then they basically centralized this stuff again well there's a few ways you either have different incentives and saying that for people to participate in the system you have to make stuff for free and open for the commons and that's already deterrent for many multinationals other ways could be saying that well we have a tribe and we set up a local governance system and in order to become member of this you have to be part of an open public society rather than part of a company so what we want to avoid is any type of threshold for people it has to be a permissionless system as a bottom if you create the internet you're also not excluding big companies because they basically build it so the protocol itself is agnostic local governance systems could help choosing what incentive schemas you want and what not thank you for your presentation at some moment you mentioned a secure sandbox as part when the fore notes that actually execute how do you ensure that there is no data leakage at that point and if this sandbox imposes some sort of constraint on the complexity of what you can run inside them I think you summarized the trade-offs really well we've been looking in things like SGX and NPC and I must say SGX has a memory requirement that's just not feasible for big data I think it's 265 megabytes you can run in the enclave and that's just not going to work having no data escapes, for example if you have a one nearest neighbor model that you send to and basically it maps out the real data onto these model parameters and sends it out again that would be a kind of an attack through the model I think just having common practice in saying if you are sending data or allowing access to data in your own secure sandbox make sure it's minimized, make sure it may be already clustered or aggregated what you can do and a few of these things that we are doing is curating the templates of what are the typical types of models that at least enforce an aggregation function for no raw data escapes but more seeing first make sure that the end layer of your model at least has an aggregation function that it doesn't also have the raw data points exposed in the end I think it's the responsibility and also the right to choose where your data goes and how you treat it at least these sandboxes are running on the provider's side so that's where you can do any if you don't want to leave your premise in the end then you just block it thank you very much and I want to quickly thank all speakers for their thoughtful insight on their data work thank you so I'm going to hand you on to the safe hands of Carmen for the panel but before I do that Sonka has reminded me that tomorrow there's a chance to do a 10 minute open talk, comment review feedback demo so if you're interested in that speak to Sonka or see the website and with that we're going to organise a panel led by Carmen, thank you to start actually I thought my role was just to sit here and look pretty but I guess I have to ask some questions too so I guess before we start so I'm actually a researcher I tried to build also some kind of data infrastructure for computational chemistry and it's a difficult problem so infrastructure is not a sexy problem and actually nobody really cares about it so the question is like how to get money and that's also how I ended up here and looking at decentralized solutions so I think I would like to say that I'm not also particularly how to put it I think decentralisation is probably more important than blockchain because science is fundamentally decentralised activity so we need to I think develop infrastructure which supports this kind of effort so it doesn't matter if you are from Brazil or Max Planck you should have ability to access data from anyone in the world so how do we do this and I guess what are your thoughts about that who wants to start Dennis? Hello, hello, yeah my interest in in preservation of scientific data came from interest in open data so like in Ireland we started to when we introduced the Irish government to the concept of open data there were exactly zero open data sets and then like probably in 2015 when there were a few thousand data sets we asked the question how do we know that first this data needs to be trusted and secondly how do we know that it will be available tomorrow and we started to think about how to employ those distributed technologies for preservation of this data and coming back to my road analogy like I think the infrastructure has to be publicly funded I don't see because the projects have the beginning and the end and if you go from one funder or one grant to another as soon as you get one grant you start thinking how you get another one to keep it going and that's not sustainable so building anything starts from standards in our view and defining first of all what needs to be preserved and what is valuable in the future that would be a good start how to do it it's an open question because there is a community in Silas talking like one community will discuss research object others will work on protocols and experiment with something I don't think that those blockchain communities have enough librarians in place and scientists and practitioners and at the same time yes there is not enough people from a technological background to go and talk to the people who discuss research objects and protocols also I wanted to say if anyone has questions please just also feel free to ask because I think we can make it more interactive like that if you have any suggestions or if you are thinking about anything otherwise I can continue and in a way it's funny because we just had the discussion at dinner so definitely here are also some of your ideas that we discussed and yes infrastructure is unfortunately not sexy especially as you said actually establishing this is even easier but then the maintenance this is actually the tricky part that is hard to get money for and luckily I think there are new things on the horizon that I think more long term but also standards are critical and why it's not sexy is because it's effort and as a scientist, I'm a scientist myself working in an infrastructure institution now I see the issue or maybe the solution there that we have to make this infrastructure thinking sexy again by providing cool tools currently people cut out images, put them into PowerPoint and store this as their data and this is ridiculous this is just generating breaks in the scientific workflow and if we can convince people that these cool tools help them to make their research better, easier, faster and more reliable then they might gain the interest and maybe also their money but they tell the funders and by the way I need more of these cool tools in order to make my research better so in the meantime do we start first making these tools or actually mobilizing people to actually ask funders to support making all these tools it's a chicken egg problem clearly my approach would be start with cool tools that you build from stuff that is around and sometimes you just have to put stuff together just to show if you do it like this you save already some time I hope so Any ideas from yeah I mean there's a lot of cool tools already that exists like think about the Kaggle community and all the bounties that are open there and the challenges and basically working on honor and rewards functions okay I guess then let's reformulate the question how do we make researchers use those cool tools well I mean popularizing these things in university shouldn't be too difficult to give them a bit more time or make them like what if research bodies or funding institutions create such kind of challenges for people to solve but that's kind of the problem because it is difficult because nothing really changes or it changes very very slowly so some cool tools have existed for many years and I think I gave an example of Google Docs so Google Docs exists for many many years and still I personally got like version 12 of a word file then version 12 and then initials who has changed so we don't even use Google Docs to actually write papers so I think cool tools are developed in the outside world but we are kind of stuck like close to the I don't know paging I remember like I did five years of research and indeed I got those version 12a from word file in email and then I had to change all the styles and it was a mess and then you open it on your windows machine and it was a no we don't have researchers don't have windows but I did discover bitcoin when I was researching and other type of cool tools or emerging things so yeah I guess that's more inside of the researcher his ability to become more he or she to become more productive or use tools that are enterprise grade or I don't know yeah have to change the mindset of a researcher I don't know it's also a legacy problem I think because yeah there's no one that always brings us up here I'm just let's play a thought experiment you guys are all researchers you get into your office the first day you need to do a bunch of experiments you're probably going to spend 14 hours on those experiments what are the actual problems that you're having right now to your life for you to feed your family so it's funding right what do you need to get funding if we go back to first principles about all the things that you do every day as a researcher you all were researchers at some point don't forget that then you find the solutions then you know what the actual problems are and then you can actually find the solutions getting a researcher to change their mind it's not hard but what's the point if I'm going all I want to do is look at collagen forever that's the only molecule that means the most why do I care about blockchain well that's exactly the thing so you shouldn't care about all these things at all but you have to because at the moment there are no other tools than the existing ones so that's why you have to think constantly about funding and publishing because that's how the system is designed so we need to change the system but the question is how and we need to change exactly if tomorrow let's say we don't have to build anything new nicer essentially so that you don't it goes back to actually making people nicer so you don't I don't know publish crappy papers for example that also so you don't need to so you don't have to publish as much you don't have to maybe chase so many grants if grants will last longer than a year or two so it's also about how do we support research and the truth is we don't so I think this conference is about actually finding possible solutions like how can we support research and not in a way like what can we do to fix the current system but my thinking is like what can we do using this new technology to actually make something new and different and actually more aligned with you I mean personal values of the researchers which is mostly like curiosity and like that yeah there are people who are interested in college and for example and why not let them to actually spend their lives researching college and but you can't do that doc you have to research that and then few other things that are that you know that will get funded yeah well just to tap into this a bit what I figured is that these decentralized communities is all about the communities themselves and what blockchain brings is not only just a community of messaging it's also a community of sharing actual value and redistributing value and getting provenance so the actual tool is community building and if you're a researcher that doesn't care about what other researchers are doing just go for your next publication then you're probably going to have a hard time anyways so if you can live in a college in community where you share insights and issue mutual rewards or whatever you have I think that's basically the start no community thinking there is a solution researchers work really well if they have a mentor and that's not a new concept but maybe the mentor needs to be the person that has that link to blockchain so the researcher doesn't have to get involved in that aspect there's somebody who takes that away and does something with it so you have a bridge well that's a really interesting comment so something that I when I look at all the solutions in blockchain space there's a lot of incentivizing of peer review which I think is a futile effort because there's no need to incentivize peer review people will gladly criticize you but mentorship for example is very important and nobody is looking to create incentives for people to be good mentors and it's something that will first well essentially because researchers are so overwhelmed and something is going to give and this is one of the first things because you are not really rewarded to be a good mentor so a lot of researchers actually or young scientists are not really being mentored very well so that's also one of the things to look at but in terms of I guess data I guess that's again a different problem so it's all kind of connected but how to solve everything in one go I don't think it's possible so we need to try and experiment I think this is all one big experiment so we don't also have to be overly critical because it's very young technology and many things will fail I guess as well but maybe something good will come out of it as well to have a chance we can create many technologies but they have to be used and for them to be used it has to be the solution have to fit into researchers workflow and you shouldn't think about what blockchain is and how it's saved it's not your problem you want to build career and to feed your family and to pay you like to buy a house whatever like you want and it should be possible to do on data attribution and like right now there is increasing demands whether from funders or from European commission for example if you get more than certain amount of grants or in of resources for research half percent of it needs to go for data preservation and each and every proposal has to have data management plan so that's one incentive how the solution and how the tools will be built and how obviously there is like different disciplines and different tools required but it all needs to be built on like all those tools needs to be built on protocols and on they have to be interoperable right interoperable yes because if we want to have a chance to employ artificial intelligence data learning or I call just algorithms they're all driven by data and if you put rubbish in you get rubbish out so maybe James can tell us a little bit more about this linking data and creating knowledge graphs so a couple of speakers comments from the floor we're all researchers but we're all different types so I'm in different camp I think for most because I'm the citizen science DIY do it yourself so we have a completely different view and I sort of call this like the equivalent to the unbanked in Bitcoin so I think we will go for this over an identity sandboxing approach so this in this extreme form it just eliminates the data infrastructure problem because we don't share any data we keep it to ourselves but it puts all the onus on the computation as Dimitri said and that's still in bionic form but I think WebAssembly will come and give us that security in terms of even as a citizen science I do it with wearables the use case that Conrad mentioned and I've got various types of brands of devices but they're all heart rates right so I have to unify the heart rate data type and so tomorrow I think I'll take one of these ten minute slots and talk about a coded project pseudo coded talk through project called heart chain that guarantees cryptographically across the community a data type and a data type and then encrypted to the raw data coming off a device and the third thing I would mention is that there is a lot of money and data you only have to look at the ICO of Filecoin and those people do reach out and come to our events to be fair but I would say we're getting a very tokenized in contribution from them because I've got some heavy engineering to do my back to them is that if you may deliver a solution but if you do it in isolation from the science community it may or may not be the right fit for us and I guess I also have one more question probably for Dimitri and Conrad and I think it's also very important one and that's data ownership so it's very complicated so universities make claims on your research data you have certain rights to your data then there are like national legal there's national legal framework funders make some claims so like who owns it in the end and what are your thoughts on the problem well that's definitely a tough one I mean and you what is missing also the patient right if you have kind of a clinical study of the patient in there in the end it's his or her data and he or she might donate this but maybe to a certain restriction for that piece of research but maybe then another one another research that pops up that would like to reuse this that's a super tricky issue and it's also between different jurisdiction different countries this is super tricky and I even think we've once we have the technology solved this will be one of the biggest issue harmonizing this in the different countries I mean with a European Union you might have one chance to get this done in a right way but I think we are far far away from solving this unfortunately yes I have two comments one is regarding the blockchain solutions which are now designed for helping science we hear different stories and they sound like they are the ultimate solution what if we have a solution which is based on different blockchains or not blockchain based solutions but they are interoperable we did not hear so much so far about this that there are multiple ways to solve this problem what if they could intervene with each other we can choose one solution that's completely fine and we can retrieve data with the other method is there a possibility for that? I think that's probably the solution we should aim for as was mentioned before every research field has different needs and we don't need the same tools so we should have something that we can actually customize to our own needs but we have to make I think we should allow these different platforms are able to communicate so that they are interoperable so for example that chemistry researchers can communicate for example with medicine researchers right about drugs and patients data so that can all but we don't necessarily have to use the same platforms because obviously we'll have different requirements because chemistry research has different requirements compared to like patient privacy and clinical trials for example but it is connected and I think that's how we need to we need to make it flexible and interoperable and I think that's the that's the key and now whether it's based on blockchain or something else I think it's less relevant as long as it's possible to exchange the information yes I agree with that and the second comment is that we heard the technological part of it and we hear that we want we want scientists to go along and use these fancy tools why don't we take scientists into the development why don't they choose what they want to do with it that is a very good comment and as a researcher trying to build infrastructure that's what I came to realize because oftentimes you have funders who kind of hire someone to develop certain tools which are then completely useless because they are not really developed with researchers for researchers they're just here there you go use it and it doesn't really fit into the people's workflows that's why I said it needs to be flexible so people can customize it but it also needs to be easy to customize so you don't have to go and learn everything about the blockchain it should be possible to just do it in a very or even have dedicated people but then we go back to the problem of maintenance and support for the infrastructure which is just it hasn't been the case up until now so we have a unique opportunity to actually build something new and different and think about what it is that we actually want to try to copy the existing solutions and put them on blockchain which I think would be a very bad idea May I add to those points I think this was done in the previous time that the solutions were put out there and now the scientists just have to enter and play around and they didn't come so this is the issue so I think meanwhile also the funders see that there has to be a community driven approach to that so it's not that you just build infrastructure by yourself but always a community needs to be embedded in these decisions and regarding your first question it's well having just one single solution would be great but I doubt that this will work out we need to have kind of an agile approach because we don't know where we end up so we need to have different solutions and then kind of a selection of that and consolidation of stuff that worked out and that didn't and keeping the chance to communicate between these different solutions would be then essential for that and a solution for the best solutions and it's still kind of research where it's science right we don't know currently where we want to end up and it's an open question and this is why we have to play around in different sandboxes and I guess I have one more question for Dimitri regarding the ocean protocols which I think is really exciting and interesting idea but how do you plan to actually bring people or do you have any what are you doing to actually engage people into using it spread the word so well we have a lot of bounties and ambassadorships and all these things basically saying that if you contribute to the network you become stakeholder in the work you get equity early mover rewards and there is a lot of basically gamification around that as well also like doing all these things it's working, it's perfect we have we issued in the last two weeks we issued three bounties and they all got already within 48 hours they got fully accomplished and we issue our native token so I think for us it's like an initial experiment but very promising I want to mention about interoperability and other things it's very important you have to look at what's the trade-off in each situation do you want consistency, partition tolerance availability of resources then you have to choose different type of tools but I think the clue to all these things is a form of abstraction like you would see for example how the internet is built there you have like the OZ model you have like seven layers of abstraction such that it becomes a very flexible system where every configuration it's possible and you don't have to care about the underlying network just abstract it in such a way that all these components are seamlessly working you don't have to care about how your model works in order to send a packet over it in order to create a connection in order to send an application due to an HTTP request it's all different responsibilities and I think that's really how the decentralized stack is working out creating those levels of abstractions what we are missing is the end game of the user experience because that's where the bigger companies win that's where the Googles and the Facebooks are stellar they create the user experience that's less worse than what you see for example I use GIMP instead of Photoshop like honestly I'd rather work with Photoshop but yeah you get GIMP and there's a lot of these things that are in open source and from researchers that's UX and that's basically also where most of the bigger companies get their advertisements in between or what have you the user behavior steering function so if you find a solution for that maybe we also have a lost mile of open source towards the end user I think we are running out of time but yeah definitely we need to invest more in the user experience which is for some reason completely neglected in almost every research application thank you for your attention and if you want to talk with any of us just grab us in the coffee break oh 30 minute break cup of tea coffee lots of more conversations yep thank you bye 10 minutes to 5 we're back okay okay hello okay we continue I just want to announce that we already got a lot of stuff done but we have to like address like three more serious working talks and then I'm not saying that the pre-dinner talks won't be serious but there will be also even more serious okay so be very bored later on okay and now I'm like handing over to Dimitra and test okay you can hear me okay I think we had all a great morning till now let's say a great day and we heard a lot about blockchain for science and I think now it's a little bit it's time to see how we can use actually blockchain in a different way for life sciences it's quite similar but we have a very nice speaker Jim Naus who is called Syncrogenics and they create a large scale distributed ledger and without words I would like to give the words to Naus to introduce his company and what they are doing thank you yes thank you thanks Dimitra I've actually known Dimitra for quite some time and we actually talked together in Switzerland beginning of the year so it's been interesting to see the development around this space and it was interesting this is my first time to Berlin and just going through this conference I realized that there's a lot of maturity already so I actually tuned my presentation a little bit because I wasn't quite sure where we are but there was some really good conversations and hopefully we'll just add on to this as Dimitra mentioned I work for a company called Syncrogenics it's a private company in the life sciences industry and there's basically building very large scale open technologies very much with the idea of interoperability by design machine readable data by design and very much this idea that you can build large scale sophisticated software small APIs and that's really the core of what we're doing and it's very much in line with the work that I was doing prior to this this job that started at the beginning of this year I was the chief software architect at the center of open control and prevention in Atlanta and during my time there we developed what is now in the open domain as open CDC so it's very much along those lines Anywho so I'm not sure about Germany or Europe as much but certainly in the US when it comes to proper healthcare there's a question of do you have the means do you have enough wealth so there's many articles just news about this do the poor deserve healthcare and at times the data actually doesn't back it up because they can't afford the medicine they can't get the treatment on a timely basis even their information isn't really received on a timely basis there's lots of examples this is one that I found personally kind of egregious is from CNN just a couple of months ago this pharmaceutical company CEO decided that it was a moral requirement not just profiteering to price couch and you can go and look it up and increase the price for a bottle of medicine for urinary tract infection to about $2,500 for bottle so I don't know if that's a moral requirement but I think the way it is right now at least in the US they're able to get away with it and I think that's something that is very problematic of many other problems that are in the space such as it's largely opaque people don't really know where the prices come from the information flows slowly there's a lot of inefficiencies I think most of you guys know this here's the top 10 most expensive medicine in the US that's a lot of money for one bottle of medicine so before I go much further who in here is in the health or pharma space alright about 5 with 6 like you guys probably know what I'm talking about and I've talked to Dimitra quite a bit I know that there's some similarities and there are some differences between at least here in Germany and what we have in the US one key one is this in the US we don't have this idea of a universal ID so if I happen to have 7 different providers and they use 7 different systems I am at the very least 7 different people under systems there is no ID that ties me together I think in Germany at least that's not as much of a problem but in a second you'll see why that is a problem as we talk so anybody heard of you've all heard of Moore's Law yeah who's a technologist here by the way alright good maybe 30% of us that's excellent so Moore's Law is effectively now just getting faster and better every 18 months give or take who's heard of E-ROM's Law ooh that's good they usually have like none or maybe just one person so E-ROM is a literal opposite spelling of Moore and it's not my thing it actually exists and it's really indicative of the big problem in the industry in that over the last 5 or 6 decades as Moore's Law has led to more and more innovation more and more cost savings and doing things faster at a lower cost it's been the exact opposite as you can see with the blue line in pharma and life sciences where the return on R&D research and development has been declining and that is one of the reasons I alluded earlier about the price gouging that's one of the reasons why companies are going to feel well maybe it's okay to do so because they're becoming less and less efficient in actually going through the full life cycle of drug discovery and doing what they're supposed to do of being patient oriented alright so how does this stuff tie into blockchain and I do want to kind of be intentional those of you guys I know we have a good group of really well informed folks here and and of course the conference title is blockchain for science and as was my title blockchain for life sciences however I think it's important to understand that if you're specific about it, blockchain really is when we're talking about a sequential linking of blocks that's really kind of where the idea comes from there's a genesis block there's a history that's retained forever however the silver ledger technology is a bigger concept than that it's similar in the context that you have data that's distributed over many nodes however you don't necessarily have a genesis block you don't necessarily retain the entire history depending on which protocol you use and for what I do and the work that we're doing we are actually implementing DLT as opposed to blockchain per se and I'll get a little more specific but just a little bit about this section and the other thing is I'm a huge believer in the public DLT or public blockchain for many of the use cases that we're dealing with in healthcare public health, public causes, life sciences and there's many reasons for this I'll get into it in a second but I think largely in order for us to build the network effect we need to allow people to join in join in a permissionless way to think about long term governance because when you have a private network it's easy to get started but if you have global problems health problems that cross boundaries cross geospatial and geopolitical boundaries you really have to think through this because if you're a little governance group of three people the three leader nodes if that worked for ten nodes would that work for ten thousand nodes across different boundaries and different geographies and different time zones and things like this and I'm a big believer that at least from what sort of things I'm looking at public is the way to go honestly if I'm being overly facetious I think a private blockchain has no more than a sexier name for an extra net ultimately you have a leader node with a unilateral decision making ability and it's opaque so if you buy into public blockchain I think you really need to understand it's way more than just technology the technology is actually the least interesting thing about it to me what's really interesting is this idea that you have a gaming theory concept token economy I think you have to really explore that particularly if you think in large scale blockchain and public blockchain the other thing is this idea of how do you affect human behavior somebody mentioned this a little bit earlier I think it was in some of the earlier morning conversations you're asking people who have been comfortable putting all their data on facebook for 15 years or however long microsecond break has been doing this to now say hold on a second the data has actually been sitting on my phone and I'm going to have to maintain some kind of a private key and figure out shared secrets and things like this that's a human thing right so this idea of a decentralized culture is not easy and it gets into all kinds of things that are way more interesting I think than just technology alright moving on so I think I've largely mentioned in fact most of you guys have largely mentioned this already so I'm not going to belabor it in the world of DLT what I'm looking for as well as security and trust everything starts with trust if you don't need to infuse trust you don't really need a blockchain or DLT because why bother I mean if you're working with seven people and all seven of your friends it just isn't worth it but I think this idea of machine-based consensus is really really important you know and hence what I was referring to a public DLT I think and again there's many different consensus algorithms and you have to pick and choose the right ones if you're thinking about Bitcoin or Ethereum as an example they use proof of work right which is by design slow by design inefficient by design it delays things so there's a sinking period by design every note has a copy of all the changes before a transaction is validated but that's not every consensus algorithm and there's a matter of ones again smart contracts we'll talk about this last but not least I think it's really think through this native cryptocurrency and again a cryptocurrency is not yeah I think the name is kind of confusing and maybe low misleading it's not just about a liquid digital asset that you can trade I think you really think about it needs to think about it as some kind of a utility token for your network that has some kind of intrinsic value or unit that you can exchange anyways I think I've somewhat of folks talked about this at length so but be anybody heard this be grateful from yeah so go and look it up be grateful it's John Oliver from early in the year so yeah exactly so the thing with blockchain is it's tamper proof right but be careful because if you put garbage in now you have tamper proof garbage forever right if one of your blocks happens to have garbage in it or if you have a smart contract that's to cut bad code in it guess what I mean it's a pain in the butt to change that so there's a price to be paid for having this immutable or I think it's really tamper proof technology another thing is this so this lovely statue here our little cat that's a physical thing right it exists it's on this table because I want to put this on the blockchain that's analog blockchain is native digital and it's virgin territory it doesn't nothing exists on it so now you have to uniquely describe this or this class right so that is not a trivial challenge at all right in the world of health almost all the health is legacy health data it exists in existing electronic medical record systems electronic health record systems many other payment systems etc etc that's so-called off the chain how do you map it uniquely to the chain trust me it is not a trivial challenge and many people don't think about this very carefully I did mention this and I think this whole idea of scaling the governance is really really really important because I hope all of you guys want to do big things you know our focus here is science and collaboration and that's a really big thing I'm working with some folks around clinical trial collaboration and it is larger scientific but we want to scale it we want it to work across the globe so think about the governance even if you start with software how is it going to work as you go from your little community to your county to your country to your region to the world you know it's not trivial and also you have to make sure it's not and again just software or people it's a combination of the two because at some point you're going to have to deal with things now a good example is the forks that have happened with Ethereum and Bitcoin now if it turns out if you look at Ethereum Vitalik has been a lateral decision making he decided you know a few years ago that who lost all this money he decided to create a fork on Ethereum is that a good thing or is that bad I don't know it depends but if you have millions of users is that a bad thing? it's a really bad thing it kills governance it kills trust so we got to really think through that anyways be grateful there's a lot of use cases here that I think I've actually explored almost all of these we talk about the tracking the generic drug supply shortage problem in the US we have a real video an example of that we've built this out but there's many who can tell me what's missing anyone? what's the big one that's missing no not quite I'll tell you because you don't have that much time if you notice I don't have anything there about a master patient index right I have nothing there that's about at least in my world in the US and what I'm dealing with and the reason is this the trigger to anything that goes to the individual patient level is identity management large scale identity management that works across all the chains it's completely unrealistic for anyone chain to be their chain that's crazy I mean we love Hedera Hashgraph but by no means expect that's going to be their chain right? and a lot of Ethereum people like Cosmos was here earlier and we've got the Lightning Network all this other stuff bottom line I think the chain of chain thing is going to happen but are you going to have identity management across all of this stuff and if you don't the idea of doing patient master index or anything at the patient level is probably not realistic at least my opinion so what you see here is largely about aggregate data largely about anonymous data largely about maybe data that we're using that's already in public form because it's already been anonymized or redacted or something like this it's not at the individual patient level and that's a key I think key qualifier alright so I like this code it's not the mountains that way it's the pebbles and the issue in my world the pebbles and the issue are data most of us in the world of healthcare and life sciences are on the left side of this picture who's on the left side of this picture dealing with internal data sources okay who's on the right side dealing with real-time data streams okay gonna mug that guy he knows more than the rest of us so but the thing is the value is on the right side if you're looking at the left side your internal updated data sources or in our case largely public data sets you're basically hindsight you're forecasting based on what you already know but that data is often old in my world of public health at times it was years old sometimes it was many years old that's not really good right I mean what we're going right now we're real world evidence and that's a big thing I think you hear a lot of pharma companies and other folks talk about it whether it's patient generated data whether it's wearable data or whatever else clickstream social media you name it you want to be on the right hand side now if you go the closely go to the right hand side as this picture proves the more value you're going to get from it in this inside continuum right and it makes sense and if you do anybody I know I was talking to several folks and they're into machine learning and AI and you know the more data you have the faster it is right in most cases you can get greater insight right there's some exceptions so that's the idea and again in our world of trying to understand a patient so the patient I think to me has three pillars of data there's a clinical data which I think most of us are familiar with that's in the electronic medical records there's a genomic data and one of our speakers colleagues was speaking about that just before it might have been Conrad I may be mistaken and then there is your lifestyle data right so if you have the three now you have the holy trinity now you can really see the insight and I think that's one of the reasons why we're doing what we're doing you know my company is because we're really trying to build systems that allow us to get to the right hand side of this I think what you'll see and I think it's already happening Facebook and Amazon and Google have largely grabbed a lot of data but I think it's also quite likely that in this distributed computing world that that could happen particularly companies like IBM and Consensus as the quote-unquote leader and governance for this decentralized computing they could effectively create the same thing that would be a terrible thing right that would be like the worst of both worlds going to do difficult things with decentralized computing and yet giving control of the data to one or two entities can do that right certainly not for health I'm a big believer in this last bullet point that we really need to create open technology as pipelines as conduit so the data doesn't move in fact in the US if the data if my medical record data exists on a particular electronic health record system most likely that system the software has a license ownership of my data and I mean they do so the ability for me to move it is not really there but the ability to create conduits to it in an open way you can do that and that's kind of what we're seeing in this space again I'm not sure how big open APIs are here in Germany but I'm guessing you guys are probably quite advanced in this thinking and the US has actually been pretty late but there's all kinds of new movement around this place largely based on the 2016 what's called the 21st Century Cures Act and it's now law that every electronic medical record and electronic health record system must through an open API provide at least basic health data for any other system to use with consent I mean it's not willy-nilly obviously but with consent and that's a big thing and that's leading to all this stuff in fact you look at Apple which is not the company you know typically think of as being open they have lots of open APIs from the Apple Watch and the health kit they can use through fire to get to other things so this is a movement and this is really kind of our thinking and this is kind of what I think of as building open software I think of it largely as what a theme park would look like so if you go to Disney Euro you pay your I don't know 99 euros to get in for the day you get a wristband right that shows you know you pay it up and you know you're yay high and you can go on a fast track or whatever if you go from the racetrack to the lake to the roller coaster the experience is different it's not the same experience yet you haven't left the theme park right the souvenir shops are the same the security guards are the same the monorail is the same etc it's the same thing with software the fact that we can have an API gateway just like a turnstile you go and you get a session token that allows you to reverse different playgrounds such as right at the very top we have data set alarmization which is what we use here on the right we have DLT apologies I slow washed out for doing blockchain type things whatever but the important thing is these playgrounds are not coupled together you could have one construction firm building your DLT and a whole different one you know building your I don't know machine learning and they all work because they all follow the open API spec and they all use an API gateway that would be a low example everybody has been to amazon.com right the homepage how many APIs do you think go behind that page anyone know any ideas not quite it's about 200 or so at least last time I looked but that's a pretty that's a pretty crazy thing though right that one just the homepage has over 200 small pieces of software in it that's why we think this kind of idea works if you're interested you're more than welcome to read this blog that I wrote by this about a year ago when I was at CDC that's really what we did at CDC that's what we're doing for open pharma it's obviously more than just functionality we have a blueprint layer which is largely open source software and we also have really the secret soft of building software in this way is DevOps modern DevOps to do automated continuous integration automated continuous development automated monitoring at the microservice layer and so on right so I won't get into like a software one on one in this but this is roughly how you do it we like to make our APIs our application programming interfaces really singular and atomic so like one API that's just one thing like get something as opposed to get it the duped parts and things like this just do one thing and do a well make it small and make it very easy to deploy and then what it looks like as an actual application is something like this so this is a real application this is our data set and my session application this is exactly how we built it and then so as an example if I take my advanced reporting API or the risk scorecard API those are repurposed in several other applications and now by the way one of the things we're doing is we have a marketplace just like the Apple marketplace where any one of you guys can go in and use our APIs amongst your own you could use our data lake, you could use our search you could use our DLT, whatever you want to do but you don't have to be coupled to the rest of the theme park you just use the specific things that you need I think that's a very important concept in healthcare it's really largely understood in technology because that's how technology has been built for a long time well at least five years maybe ten years but in healthcare we are largely lumbered to this giant monolithic applications where you make one change a year to make it that change of production and that's just ridiculous that doesn't allow you to do world data right, you're stuck and I think that's a common story okay, so I mentioned open farm a little bit it's not by any means the only one of its kind just in the life sciences space there's open CDC which is again myself and my team built that and released the public domain and there's open FDA, there's other ones as well in many other industries there's many other ones AI and machine learning spaces a ton of open AI and machine learning libraries and frameworks I encourage you guys to look into it okay, so how does this tie into to distribute ledger technology and blockchain so this is what we've done again I know it's very hard to read the details so you don't have to worry about it but really the idea is this for tracking generic drug supply problems in the US there's a cast of characters that we have to identify the FDA as a regulator they are the user, right they are the ones who want to know what's going on but then there's active and inactive manufacturers there's distributors there's group purchasing organizations that purchase at large scale and then there's pharmacies I'm simplifying a little bit but that's largely what the space looks like this is the architecture we have again it's actually pretty simple it's actually based on using asynchronous message queuing using Kafka for this POC it's using the Amazon SQS simple queuing services but we're using Kafka for production but it's a pretty simple architecture this is not that difficult what's important though and somebody else mentioned this it was in a panel right before me I was getting ready paying enough attention to the Hedera Hashgraph it's what we're using that's not that interesting because nobody really cares what they care about is what does the user experience look like is it consumer grade and I would encourage you very very strongly you gotta think noise versus signal there's so much of a blockchain and DLT that's noise think of it as plumbing, as infrastructure I fully believe that in 5-10 years there will not be a single blockchain conference anywhere because there is not a single SMTP conference anywhere SMTP is protocol used for getting your email back in like the early 90s there were SMTP conferences but it's plumbing it's the pipes that connect things so I don't think honestly I think this thing is gonna be infrastructure what's really interesting is what you do with it so this is a video of our work, hopefully you can hear the audio hello and welcome to our proof of concept demonstration of OpenPharma's generic drug shortage application powered by Hedera Hashgraph in the current version of this use case we are oversimplifying the manufacturing issues in order to show our solution to make the generic drug shortage information publicly available quickly and accurately in real time our login page will provide proper authentication verification for allowing access to the authorized profile view as an administrator I am able to view and act as all user profiles this use case contains several user profiles such as the FDA regulators who can view all the incoming information in real time FDA inspectors who can instantly create and submit inspection reports on factories and manufacturers distributors pharmacies and group purchasing organizations who can easily perform actions such as reporting new facilities updating their current status as well as report generic drug shortages on the fly going back to the FDA regulator team view here you can see our recently reported drug shortage with Everest Group you will also notice that the live feed allows all new data coming from all users to append to this list and update our bar graphs for real time updates of the generic drug ecosystem the FDA regulator team is also able to filter out results and focus on specific user groups such as manufacturers where you can view factories and inspections as well as distributors pharmacies and GPOs where you can see all generic drugs in stock or in shortage through bar graph visualization per user group as well as specifically within each facility that concludes our POC demonstration of Open Pharma's generic drug shortage application powered by Hedera Hashgraph thank you for watching I think the most interesting thing about this is really that concept we had at the very beginning that we are trying to build near real time data systems that's really the giga and that's why we chose to use Hedera Hashgraph because it's a not to get too technical but it uses what's called the asynchronous Byzantine full tolerance consensus algorithm which is very, very fast and the technology essentially gets you to a validated state of a transaction within about two seconds at about 100,000 plus transactions per second so all to say if you want to track something in real time and you want to have some kind of a DLT backend in our opinion it's a pretty good option it's not the only one by any means but it's a good one now to be clear though this is not a blockchain there is no genesis block it uses what's called the directed acyclic graph consensus there's some pros and cons with that but nonetheless it meets our needs and again going back to my comment about infrastructure if this works if it provides you a trust cryptographic trust if this provides you the speed if this provides you transparency then does it really matter what protocol you use that's our thinking anyways just to wrap it up this is kind of the roadmap if you like this is the way we go about doing this as you can see this is largely about open source open technologies I didn't mention this and I'd be happy to offline it if you like but I'm also a very big believer that in order to make this public DLT work you have to use micro payments you have to have services that can be consumed with minimum amount of payment so you get customers immediately so it's not free and you don't have an advertising model we're not trying to create another Google but the per transaction fee is very very low because you expect to have a real time system with many transactions anyways that's all I have for you thank you thanks a lot now I would like to give to the next one I'm not really sure who is now the next I see here yeah okay great I'm Robert Peters and I'm with Orchid I'm the technology director for Orchid and I wanted to cover identifying identities Orchid identities in the blockchain and so what's fun about this conference there seems to be actually a pretty wide variety of people there's technologists there's admins here there's people who know what blockchain is there's people who have no clue what blockchain is and so this presentation will kind of cover a little bit of a lot of different subjects and just if you don't understand one thing just kind of bear with it acronyms we all hate them but they're better so what is Orchid the organization first of all Orchid is an acronym it's the open researcher contributor ID we're an open nonprofit organization and we're run by and for the research community we provide researchers with a unique identifier the Orchid ID that reliably and clearly connects them with their research contributions and affiliations and you'll see an example URL that's an Orchid identifier and there's our domain and then there's a 16-dentate numeric ID that kind of identifies who that researcher is and if you click that for humans humans resolve to a record that kind of looks like a CV it's not really a CV but we'll have a list of works or different name variations that you won't recognize in your research activities we have about 500 systems that have integrated Orchid ID and that's growing quickly and those general use cases would include grant applications manuscript submissions interest systems, repositories we've been talking with open pharma initiatives it's a pretty general identifier useful for any academics scholar or research space and so we use the term researchers a lot but actually we include admins and we include other types of scholastic work so I'm going to say researcher a lot but really it's a very inclusive term for us so the researcher typically how they interact with Orchid is an institution will ask them to authenticate their ID and once that institution authenticates the ID they can use it to collect information about the researcher and then attribute the researcher correctly in their metadata and in ideal situations that metadata gets pushed all the way to other systems that include publishers, employers and funders and eventually hopefully it gets into the Orchid record and we see that nowadays with things called crossref auto update where when somebody publishes their work they're notified by Orchid that it's been published before the publisher or anybody else notified them because some of those systems work quick enough other systems don't so but we want to get there where it works that way for everybody oh yeah the technology this is going to get exciting the Orchid tech stack we are a typical Java web app so this is like a term that was popular 10 years ago 20 years ago the good news is though we're open source we have a public API that's CC0 so any information the researcher chooses to share becomes CC0 and the researcher controls what information they share and then we have a member API and the member API allows our members to write to the API and then adds on a few other things like some information that the researcher may want to share with our membership and not the public and a few things that convenience like webhooks access to the record is controlled by the researcher so the researcher gives permission to our members to read the record or push the information in the record and that's via OAuth2 another fun protocol and finally no short term blockchain plans so why am I here yeah so I mean we're kind of earlier we heard talk earlier about we just do a lot of stuff in a centralized manner and it's great why don't we just get to it because nobody really cares blah blah blah and Orchid is one example of that working but we are actually really excited for blockchain and if you want to understand why you got to read our vision statement Orchid's vision is a world where all who participate in research, scholarship, innovation are uniquely identified and connected to their contributions and affiliations across time, disciplines and borders so our mission is not Orchid is the entirety of everything that's not what we want to do our mission is to make sure researchers are connected to their outputs and so often I talk to people in a lot of blockchain people to you they hey Rob come on I want to talk to you we're doing something and we think Orchid looks like this this is what they think Orchid looks like okay let's talk some more and the reality is Orchid is actually just part of research's identity so you have your university identity you have a government identity you have a LinkedIn your social identity actually ends up being pretty important when it comes to research Twitter, Orchid record every time I look or dissect the problem there's one more researcher identity need I need credentials to access this equipment or access this collection of books and so Orchid we don't see ourselves solving that problem alone it's a community effort and really we need the community to kind of address all the different types of identity just to name a few what we do is like how do you correctly credential some of these national identity or local university identity and the social identity needs there's a lot of problems there that Orchid's actually never going to directly approach so instead what we do is we offer a researcher identifier and a record that can help connect researchers to their many identities and activities and what that kind of looks like something like this we'd really like to see the Orchid identifier used to help attribute metadata and all these systems out there and then have that metadata point to Orchid record and ideally vice versa we want that metadata references in Orchid record that we can point back to the source of a lot of these things great so now we've kind of covered the identifier and that's really the core of what Orchid does but now let's talk a little bit about how that helps connect with other identifiers, mostly identifiers about research outputs you have research papers, university affiliations peer reviews, grants equipment, researchers do a lot of stuff, conferences right, we're at a conference people are producing at conferences, how do you correctly attribute that researcher to it and every time we look there's yet another thing that probably needs attribution so researchers are doing a lot of work out there and they're not getting attribution correctly and this graph kind of shows a little bit of where we have good coverage if we're talking about works researchers actually Orchid via crossref and other PID providers provides pretty good coverage you can push a lot of different types of works at Orchid to have them correctly attributed but when you get into equipment it becomes very the community is not there yet so we're trying to facilitate building out infrastructure for attributing grant awards, equipment, peer reviews researcher resources which is a new one that's coming up but there's always another thing we need to try to figure out how to connect and attribute researchers to and currently this is just a short term roadmap of new things that most researchers are familiar with PID such as a DOI so I did a DOI, my paper is now official and they feel good about it that's the extent they know they can click this link and it resolves through their paper but we're trying to help the community develop the same kind of infrastructure for affiliation types researcher resources and grant IDs and there's all kinds of other things out there that we also need to connect to and then I used the term PID and I was like oh wait a minute there's lots of people that probably don't know what a PID is and so I tried to think of the easiest explanation I could come up with and it's a it's a resolvable, actionable durable identifiers that can be used to locate and describe things and typically we see this as URLs that exist forever and from Orchid's viewpoint we really like URLs that resolve to metadata for both machines and humans so you see some that do one or the other and we really want to do both well and even beyond the activities that I've been referencing there's lots of other things that we need to help connect researchers to there's different profile systems right you have your NIH profile and you have your LinkedIn profile you might have a profile on Scopus and so depending upon what areas you are and what areas you move into you definitely have more than a few profiles how do we even connect a researcher to their Google search results I mean that kind of ends up being pretty important in the research community so many types in the name they pop up government identities somebody brought up Researcher Gate earlier today well how do we connect that kind of profile and all kinds of stuff that really we need to help facilitate connecting to and so when you look at the scope of the problem I just kind of I'm quickly described at a high level it's huge like how do we connect all these things to researchers and Orca's viewpoint is it's a community effort we can't go to alone so we really need community initiatives to help make this happen which brings us right back to blockchain and so here's there's a lot of interesting space there's a lot of innovation going on and lots of possibilities for managing researcher identity and attribution of activities and so why Orca Plus Blockchain well the value Orca sees in it is it's immutable and distributed and when we're talking about connecting researchers to activities or activities are everywhere so I'm very distributed so having distributed systems and kind of correctly attribute to those things makes a lot of sense to us and specifically we really like we're really liking the innovation we're seeing in the verified claims built on decentralized self sovereign identifiers and also like some of the initiatives we see around tracking researchers activities with decentralized systems and we really would like collaboration on PIDs and PID infrastructure and some of those could be addressed best with blockchain technologies and so let's get down to the brass tax what are we really asking number one is if you're trying to attribute activities to researchers or attribute a researcher itself use the Orca ID and that may or may not link directly to the Orca record you could use an Orca ID or an external system the important thing is there is this ID out there where we're trying to make it easy to disambiguate who a researcher is add PID or PID like resolution to researcher activities pushed to blockchain so a lot of blockchain technology is very hard for people to understand the tooling around it is very hard you have to install Chrome extensions and buy coins and do all kinds of stuff well for the metadata both for machines and humans PID like infrastructure i.e. links that are persistent and you can click and see what the link is describing it's pretty easy for people to use and so building that on top of your blockchain initiatives as a way of having easy resolution is something Orca is really interested in promoting and then finally if you want all the gold stars push references to your PIDs to the Orca record you've developed a blockchain and you're pushing the stuff to the blockchain and then you have a way of resolving it via a link that is PID or PID like push it to the Orca record and that makes it easier for the researcher to find it it makes it easier for other systems to resolve the ID, get metadata about the researcher and see oh hey here's this little tidbit information maybe I should follow this PID to the source which probably has information that has the granularity you need for what you're describing on the blockchain and so as you guys are out there creating innovation in the researcher community we just ask you to consider the ways you can interface with Orca, collaborate with us and kind of help the whole community disambiguate and attribute researchers correctly and that is it Any questions? One question or one statement so thank you very much for clarifying the difference between identity and identifier and we have to solve the problem of identity if we don't solve this problem then we don't need to talk about blockchain and the advanced concepts that we want to archive like money distribution maybe pseudonymous publications and all this stuff and this brings me to another thing identity files are fine but they are like at the moment there's no high pressure on them to be really one single identity Orchid you almost call identity because there's no incentive to create 20 or 30 Orchid IDs as soon as we start to distribute money and economic pressure on something there might be much more incentives to create socket puppets like fake identities and are there like how many people check whether this is a real person at Orchid well nobody checks if it's a real person so we can just like create I can create 20 Orchid IDs that is possible I know my friends at Research Gates they have like people looking into identities that you don't create fake identities because they have another interest the differences is right Orchid there's a couple different ways we approach this number one is we have members and the members can authenticate an Orchid identifier and push information to the record so if a researcher asserts they work somewhere that's great but if their institution writes to the record they work at the institution that helps you identify the person and then additionally to credentialing government credentials or you really want that really a thousand percent solid somebody showed up at a desk with a passport and I don't know your electric bill and some kind of proof of who you are what I'd really like to see is I'd like to see initiatives where somebody builds a tooling to push those things to the blockchain and provide references to the Orchid record like hey if you want that kind of proof here's a PID follow this link on the PID that PID is going to describe the person and this is how it should also describe how you prove it via the blockchain tooling so if you're using sovereign self identity here's a link that I click and I go off the Orchid record and I see some data there really is some kind of blockchain some kind of sovereign self identity and if I want to prove it myself this is a trust note I go to to verify that fact that tooling is in development in the blockchain community so Orchid is asking for references to things like that to be pushed to the record but we're never going to approach doing identity in ourselves because we're in all the countries in the world in one facet or another and then we get into regional problems local problems and it's not the goal of Orchid is to provide an identifier to help with disambiguation and attribution not not the end all to identification so really that's a perfect space for a blockchain to approach a problem yeah sorry this was not like that you never advertised that you're doing that so that's completely right but it makes completely sense so we have to work together with other entities that basically do it anyways publishers research institutes networks and so we're always out there trying to get direct relationships with membership who can push metadata records so if you need a source from publisher let's forget the publisher let's go to the journal level he can get attribution at the journal level great and then somebody goes and looks at your record they're going to understand what's going on thanks great it was almost the same argument so mentioning the concept of self-sovereign identity verifiable claims the W3C community draft about this and so on the response that I got felt almost hostile so in the meantime they developed something and I'm super glad about this this really sums up and one more concrete question or suggestion how about as a first step so to say in the ORCAT record for crypto addresses so that you can store certain public keys in your profile to make it easier to have a machine readable verification of claims and things on chain yeah that's definitely something that we're always actively looking at one metric though is actual researcher uptake is always kind of a hard metric to pass on some of those things but yeah we're always iterating on what metadata can be pushed to the record and you can push person identifiers we're a person identifier you can push other person identifiers and so if you have a credential and you frame it as a person identifier there's already a place for that click it to go off and see it but yeah so pushing into some cryptographic patterns stuff like that so the iteration in ORCAT we're always trying to grow we're always trying to improve and we're open to collaboration further questions otherwise thank you very much again so the next speaker will go down very very at the beginning of everything the data generation so how to connect the blockchain actually with the internet of research things looking really forward to that yeah so this is a quick overview of the tech we've been exploring it for me and then some food for thought on how to apply trusted computing to scientific research so down to the data generation acquisition phase so we've heard that obviously in recent years we've had lots of hacks and incidents of surveillance compromising user privacy and mostly due to the centralization of big tech companies oops so yeah this recently came out Bloomberg last month about supposedly Chinese military adding chips to super micro servers and that's a Chinese company that manufactures servers that Apple, Amazon and big tech companies buy and then deploy in their clouds then Apple obviously refuted all that so we're not entirely sure if it's fake news or not but the point is that they according to Bloomberg the Chinese put this super tiny chip into the servers and that kind of chip was being used to secretly add instructions to the CPU that allowed basically China supposedly to eavesdrop on clouds communications so obviously Apple the big tech companies are having their own solutions regarding to privacy so Apple has been pushing the envelope on this both on the consumer side on the hardware and on the software side so on the consumer devices they have this T2 chip on MacBooks and the A7 and on words chip on iPads, iPhones and also the Apple watch so what these processors have is a co-processor that includes a secure enclave and what that is is basically a hardware filter that would act as a barrier between even the CPU so the processing unit in your device and the information in this case it's used mostly for face ID touch ID data so the biometric information that you give to your phone is never being accessed even at the hardware level so obviously this is kind of a secure system this is the main architecture so yeah the memory even can access the metric data that you give when you access your phone in that case on the software side there's so on the software side there's a thing called homomorphic encryption Apple in particular is using something a step behind this which is called differential privacy and it's about anonymizing data sets before at the data generation event so on the device itself that is actually sent but the problem with this is that recent research has shown especially this year that these data sets can be de-anonymized so it's not the most secure method that we have these days so there's another step after that called homomorphic encryption and what that is is a cryptographic approach where you can do computations on the actual encrypted data itself the problem with this it's mostly academic approach so it's very slow even though this table will show you when these use cases could be implemented especially in healthcare in one or two years because the point is that data is already encrypted at rest in transport like SSL TLS and address is using databases but the problem is how do you encrypt data efficiently when it's in memory so obviously with homomorphic encryption you don't have this issue because the actual computation is happening on encrypted data itself but it's very basic operations like addition multiplication so it's still a research area so this is a practical use case that you would have I think in the talks before we got a similar scenario for healthcare data and in practice what happens is that you encrypt your blood sample in that case with the private key then you send the data to the server and then you have server-side processing using just the public key on the encrypted values and so when the server sends the data back the client actually decrypts using his own private key so everything is happening with encrypted data so the big tech companies are having their own approaches to this especially Microsoft and IBM they have released this paper a while ago called Pinocchio it's an approach on trusted verification and this is like it's not an academic effort it's actually a much faster approach so it's the concept also behind the well-known in the cryptocurrency space ZK's NARC so zero knowledge proofs this is a different implementation but it's using the same underlying approach of verified computation so it's a much faster implementation because you can take a program run it on an untrusted server so let's take the example of the super micro hacked server and then check the output with a proof and this is all happening in software yeah then you have Amazon side trail there is another effort from Amazon doing the same stuff but yeah in the blockchain cryptocurrency space those are the main efforts for this kind of stuff so you have a crypto note the crypto protocol that is Monero basically as a cryptocurrency and that is basically using ring signatures to to protect transactions like last month they added research coming out of Stanford called bullet proofs and they actually implemented that and on their blockchain which would reduce the size of the transactions a lot so this is research happening really really fast and being implemented in the real world and after that we have zero knowledge proofs and that is probably the most interesting development in cryptography because it allows you to prove like you have basically a prover and a verifier so the like in that case at the data generation phase you would like to transmit that you actually own that data without revealing the data itself so that is the zero knowledge part and yeah the cryptocurrency Zcash implements that for financial transactions and then one step after that is what is called T's so like trusted execution environments and that is you have that let's say implemented in hardware wallets but in particular you have project enigma from MIT that is using this technique to create basically secret contracts on Ethereum and so using the trusted execution environment what that is is an implementation mainly from Intel called Intel SGX and it's an isolated environment inside the CPU where developers can actually have reassurance that the code being executed at the hardware level can be tampered with so that's how they basically create privacy smart contracts on Ethereum and then the last advancement in the space is called ZK Starks coming out of Starquare which is another cryptocurrency company and basically it's the last version of zero knowledge proofs but instead of using asymmetric cryptography and a trusted setup like ZK's NARCs uses symmetric keys specifically collision resistant hash functions yeah and that is much faster, better, etc so yeah as I mentioned you have hardware wallets that have a similar implementation in terms of having a secure element inside that acts as a hardware filter between your private key and the execution so yeah this is similar stuff as what Apple does in their phones so all of this is the state of the art of cryptography and trusted computing this time but the idea of applying all that to scientific research would be to going from bits to atoms in terms of applying all that to companies like Transcriptic this is a Bay Area company that aims to be the AWS so the Amazon Clouds of biology because what they do is put all the web lab stuff inside containers so like pipetting all the biology web lab processes and automating that using APIs so what you can do with this is you create an account as a biologist and then with code you automate all the stuff that you had to hire like 50 researchers to do in the past the problem with that is the pieces in terms of the data acquisition and the generation phase so how do you trust that these guys are actually performing the actions that you tell them right obviously if you have your own research team you have your own eyes to check on all that but if you outsource and delegate all that possibly mission critical research to something like that in the world how do you trust that this research and this data has not been tampered with has not been compromised has not been like they changed the process that you delegated to them and all that so the main idea is obviously to apply all the previous techniques including trusted computing at the hardware level on these chips on these manufacturing facilities to really go from bits to atoms and complete the pipeline of unautomated like AI science research and all that so this is the let's see if that works this is just an overview of their lab so there's a robot that automates in that case the pipetting and you can code all that save tons of time so there's a few missing pieces right in terms of the final vision would be integrating all these processes into one pipeline where you can go from your jupiter notebook and your like web lab notebook to this and the next video is the fundamental way in which we conduct our lab research really hasn't changed that much from the days in our store the present actually looks a lot like the past as I like to say there's much more voodoo in science that anyone is willing to admit we want to eliminate that stuff as much as we can people would print out pictures and tape them in their notebooks and expect that to be the way that like data is tracked and passed along my grandmother was actually a chemist back in the 40s I actually spent some time reading her thesis it was hard to tell whether this was done in the 40s or you know today most organic chemists think of themselves more as artists than actual scientists you get things that look more like food recipes like at a dash of this and a dash of that it's very hard to reproduce finally someone sat down and said like why don't we just take the experiment and turn it into code the equation that we generated is an emergent property of thinking about how to move the science forward in the most effective way possible the emerald cloud lab allows anyone with a laptop to direct experiments from anywhere in the world it's also an automatically parcel information to store it so you never have to go searching through old notebooks all the data is tied together a robot can do a lot of scientific techniques better than humans can and all of that can be described in code and database it's very exciting to be a part of that there's no need for people to be in the lab to actually run the experiment or to have access to the data it's usually available to anybody when we noticed that when we started going to the lab in the morning and there was no one in it yet to all these things we're running because everything is standardized do you have all the information about how you carried out the experiment the first time you can very quickly reproduce that data over and over again and fully reproduce and be fully encapsulated that means you can basically abstract a value that you can build on top of that the ECL allows us to answer much bigger questions in biology that we wouldn't otherwise be able to answer it allows you to be acting as the architect of the science rather than actually carrying out the experiments themselves because everything is automated we're not doing this just to do it we're doing this because we think that the way science has been done is not rigorous enough so one of the ways this is going to change life sciences is by making each individual scientist much more powerful you're only limited by the experiments that you can dream up there's this great quote about standing on the shoulders of giants and that's how we make progress in science I think that kind of undersells it a little bit but we should be standing on all of each other's shoulders yeah that's it questions hello I'm over here a lot of science I think involves not putting things in the code but actually observations that arrives very like in a very serious serious manner so how would it work in the situation where it divorce the scientist from experience of natural processes and it's all very pre-programmed pre-determined how would you discover in this kind of ecosystem definitely that's a good point and this was mainly let's say to automate the second step of the scientific process so the first step you mentioned is the idea generation phase so after that you would then go on to verify that hypothesis and go on with the process and in that instance in this example for like wet lab biology you would then verify your experiment and maintain your experiment using these techniques instead of going through the process that we know about like hiring I don't know like 10 PhD researchers if you don't already have your own lab so this could obviously open the door to lots of citizen science that today is mostly related only to like data crunching and stuff that you know you have initiatives like bio curious in the US and iGEM so that citizen science scientists can also do wet lab research on their own but it's very very limited right so if you have this kind of pipeline completed it would open doors I would say that most sure sure but that's exactly the point so sure sure so this would also tackle the reproducibility crisis in that specific case for wet lab experiments so as they mentioned in the video like they're still in chemistry some like processes that look like food recipes right so if another researcher wants to use that experiment it's very hard these days in terms of you know the actual wet lab stuff so with this it should standardize to a certain extent where the reproducibility just comes after like you click another button and it's done but yeah sure yeah that's absolutely right in fact yeah absolutely in fact that's so the missing piece in terms of this is like these are two companies in Silicon Valley right now and like for this vision to work you would need I don't know like those and at least of other such things around the world so more of in a decentralized way absolutely yeah Hi Max you had exotic blocks going from bottom left to bottom right with all this fancy encryption I was just wondering was a box not on the slide to the bottom left and that was the lightweight cryptography to allow you to couple from the sensor or from that lab actually into the infrastructure so I just wonder if you have any thoughts on the lightweight encryption that we can use actually on the devices yeah for lightweight stuff it's hard like you can't use as you know omomorphic encryption and so things like this are more practical I mean obviously big companies created this kind of stuff for cloud computing but they're supposedly efficient enough to be explore for mobile clients too okay for other questions otherwise let's thank all the speakers once again Zürger how do we continue thank you very much everybody and this was already an awesome day we had a lot of fun and now the fun starts okay no no no just joking so to wrap it up we were totally destroyed like what blockchain means in science and then slowly we built our way back like when two definitions had this beautiful future of like new data handling concepts tangled healthcare real world blockchain interface problems of course identity identifier as a real world interface problem with blockchain then the lab stuff the trusted hardware things we went into cryptographic concepts all the way down and now we are going like into research culture and into space and then we like evaluate the mathematical description of knowledge and then we go to the untrusted third party okay and but I want to first explain you in one minute the graffiti art it's actually a street artist and I felt very honored from Berlin and you probably know the Teufelsberg the radar station yeah I asked him where all the graffiti is are and the graffiti artists are so I asked him Tobias so if you want to spray there who have you to ask and what do you need to do can you just spray over other people's graffiti and he said to me no no no the others have to ask me whether they can spray there okay so he is one of the street artists in Berlin okay so well this is a blockchain we have monetary incentives there is a token there is a dollar sign on it so we have game series it's a dice over there then of course who knows where the 3 is standing for the 3 might be huh what might be the 3 the trusted third party right the 3 and there is a wallet what might the wallet be and we are breaking open a wall and the male researcher actually I want to apologize for the very clear definition of male and female scientists actually the female scientist is looking into space where we have to go at some point right because we cannot we will not solve all problems on earth forever right if we go to space we will make like human life available to so much more people doing the existence of our race then if we just stay on earth and worry about the problems here on earth I am not saying that we should not look into global warming and everything so we have like two futures there at first sight they all look beautiful right on the horizon but there is like one island is dying and one island is doing good right and in between these islands there is a black swan a black swan that needs to be discovered that's all important stuff that we are doing right and we should be crazy and like come up with really cool new concepts and crazy ideas and this and that's why I also love this last session but ok we have to go down to earth is there a question to the oh well I forgot one important thing there is a cap theory right in the upper right corner is consistency availability and partition resistance dash decentralization right so we can only have two of them right so you will never ever forget the cap by the graffiti street artist cap over there ok so and it's a serious rocket not a Saturn 5 yeah ok I just want to mention that ok we go down to earth and we have down to earth again we have like the best poster awards and then the research culture keynote by Laurie Professor Rajendran thank you very much for your attention so far and ok see you us ready ok before I give this talk I am I am asked to announce the winners of the poster award so we there were tons of posters astronomical number of submissions for poster right there were a staggering 7 posters and it was really really difficult to evaluate this so I couldn't do it on my own so I was helped and assisted by Lambert Heller Alexandra and Benedict by the way so if you could all give them a hand that would be great they did it's an arduous task to evaluate this poster and all 7 of them if I had money I would give it to all of them and but since I don't I'm a poor professor from Switzerland and London so the 2 posters that we selected as some of the best all of them were pretty good the averages were pretty close by but the 2 were fantastic and the first one is by Moritz Schubert repurposing open source tools from Bella Gibbs Wuppertal group by the way give them a hand present his poster tomorrow morning he or she has to present it Moritz is a good, I hope it's a guy and the 2nd poster is to Eva Calmar on blockchain readiness from the TU Doft so great so it's easy something is happening there when it's getting fixed let me introduce myself my name is Laurence Rajendran I am a professor of neuroscience at a king's college in London I used to be a professor at the University of Zurich I just moved to King's to be the deputy director of the dementia research institute which basically aims at defeating dementia in 5 to 10 years so I'm a practicing researcher I work with data scientific data every day I work with a lot of researchers who are fantastic but this also allows me to see the good in scientific data but at the same time there are also great things in the academic world and so Sunke has asked me not to give a scientific talk today but he in our he's asked me to give a talk on the 2 startups that I have, thank you which are Science Matters and Eureka Blockchain Solutions which I will touch upon it but we're going to tell you a little bit about the epistemology of science the way we do science and the reason why we do the things that we do and so before I start let me ask you how many of you know this story about or the jokes on about 2 cows and capitalism oh nobody that's great so that's the there's this traditional capitalism as you know there are 2 cows you have 2 cows you sell one and you buy another bull you heard multiplies and the economy grows you sell them and then you multiply this income this would be the French you have 2 cows you go on strike organize a riot to block the roads because you want 3 cows this is the Swiss capitalism which is you have 5,000 cows none of them belong to you but you charge the owners for storing them you know where I'm going with it I'm Indian so if you're an Indian corporation you have 2 cows and you worship them I want to tell you the insane mad co-distan where John Tennant introduced today which is really you have 0 cows right you give 1 arm and a leg to people called publishers along with data idea all of that and they might you know they might publish your data and this is an insanely capitalistic market and that's like billion dollar is just only in the English speaking English speaking scientific publishing and academic publishing and there are like more than 50% of the margins and I want to tell you this there were these 2 tweets this guy called William Morgan he said 2 academics walk into a bar they bring their own drinks and then they pay 5,000 dollars and then John John are you here he's not here and that's not really great but this is what the metaphor that he said this morning and this is it comes almost close to what we are dealing with every day not only we as scientists in my lab we not only read these papers come up with great ideas make observations great hypothesis not only we ask and write a grant we have to write this grant this is like a strenuous process we have to write a grant to the funding agency where you as tax payers give us the money and we we curate data we work on experiments and we make discoveries findings and then and at top of it we provide this data to a publisher who then says that maybe this can belong to a scholarly space and we have to pay something like 5,000 dollars to the publisher not only to create this knowledge there's this barrier to create but at the same time there is also a barrier to access knowledge my university in Zurich pays around 5 million dollars per publisher per year in order to just give us researchers access to the knowledge that is created by tax payers and researchers and so that's something this is extremely important to know the economics behind publishing and I will tell you over the time that it's not just the researchers who put these barriers but there is also another stakeholder who also puts barriers for this open science and and if you were to make science let's say even if you pay 5,000 per article and 5 million for access did we make science better did did I get a return on my investment and is it better? Actually not really science is not entirely rosy there is high degree of irreproducibility and lots of researchers acknowledge there is a reproducibility crisis not only it's not necessarily that we do science the science that we do now is worse but it's a combination of somehow irreproducibility is higher and at the same time somehow we also came up we are coming up with tools to detect fraudulence and detect misconduct better but it nevertheless says that there is a crisis there is a crisis in terms of irreproducibility and irreproducibility could come from many different ways it comes all the way from kind of a how do you say a lack of robust validation of our science somehow we rush to publish that we don't really robustly validate because there is an incorrect analysis etc to some degree of something so stupid like this there is this I'm sorry about that this is from a group in Malaysia which published the cell biology paper where they show that as you can see here there are these cells they're named one, two, three and four and their idea is to say that the under different conditions all these cells have different shape I think this story went down like this they started to they submitted the paper with only four cells saying one looks like this two looks like this three and four look like this but only having n is equal to one and probably a reviewer would have asked it's not really scientific if you give me only one cell to show that one cell looks like this you have to show more cells the researcher said hold my beer and then they went and clonally copied these as you can see here if you can see it they cut this one cell and then pasted it on a black background and then showed it now you have more cells to show right you can debate why they did what they did and we will come back to this question not only questioning the morality of the researchers and why they did what they did to also ask about the system that somehow demanded this dishonesty in some ways and we will talk about this particular issue today and so it goes all the way to going to going from non-robust validation of truth or the lack of consensus that will allow me to validate what I will call it a scientific fact to something as really not very intelligent as this particular thing and this is due to the fact why do we do this why do researchers want to publish something and this is this idea that we need publications for researchers like us publications are the currency in the ecosystem that we live in order for me to get a grant in order for me to employ a PhD student or postdoc in order for me to feed my children I actually need publications this is the currency that we live in and as a result as soon as you have something like this you end up manipulating without being non-robust and an impact factor or the journal that has highest number of citations is called the impact factor and if you could publish there then many things are granted in a way when I was finishing my postdoc at the Max Planck Institute in Dresden I got a phone call which I will never forget and there's also the phone call that actually changed the way we do science and also it's the birth of a researcher a very well known researcher from the University of Zurich called me and said what are your future plans said I don't really know I'm just finishing my work I was working on Alzheimer's disease and he said so what's going on and I said I have these two papers and these two papers are now under revision and I don't know I'm just going to think about continuing this work and this researcher did not ask me what was the paper but he asked me where is that paper there was no discussion as to what the contents of my study or the science was but the question was really merely focused on where these two papers were submitted it so happened these two papers were in a journal called Science and I said they are in science and he said something interesting he said if you had these two science papers for sure you'll become a professor at the University of Zurich and I tell you what I did have these two papers and I did become a professor at the University of Zurich without without really knowing what the content of the scientific study is and I tell you what we often think about these two papers in terms of how a measure of a metric should be what a metric should be and we do this because we are all here not because we think this blockchain is going to change our lives we are trying to make the system efficient we are trying to make our lives a little bit more convenient and making sure that can we compromise effort with convenience and so impact factor came as one of these measures and not only that this would make you a professor today if you had these high impact factor journals you could get discount on a barbecue in China so this is an actual restaurant in China where it's called Lancet Barbecue depending on the last paper that you had and its impact factor you get discount based on the impact factor of the journal that you've published alright and this is very very true and so the question is what is this I think we have to discuss this we all have to discuss we understand that we are here to discuss about the potential of the technology but even when we think design and execute blockchain technology today for science we need to understand as Ulrich said this morning as John Tennant said this morning can we change the mindset of the people can we change the incentive structure of academia today and and as I said if a measure becomes the goal it actually stops being a measure no matter whatever we do this is our goal if my metrics the fact that I need to get a cell paper a science paper or a nature paper if that becomes the goal I think we are in a lost battle in academia and we go all the way even to kill people I'm not kidding this is this is there there are people who kill I don't want to sound like a populist but out of Fox News really this is these incentive structures measure against some of these the social good that we look for I am an academic I teach a lot of students and when nature published this report that collected various interviews from senior graduates scientist this actually shook me to the core says like what in many labs when people asked the incentives to be first can be stronger or it is stronger than incentives to be right and these have real life consequences when we rush to do science or our goal is really to have papers as opposed to doing science the real life consequences could be really money that it could cost us a lot of money it could also cost us delayed progress delayed scientific progress I work in a field which absolutely does not have a cure till date and this is Alzheimer's disease and but as you probably know if you read news in any newspaper this is what you see there is a breakthrough we keep curing Alzheimer's disease in every paper every cell line every mouse model gets cured of Alzheimer's disease however when it comes to the actual numbers that the Alzheimer's association sent us two years ago this is the thing that is an operate we haven't cured that the mortality due to Alzheimer's disease is actually higher and when you look at the irreproducibility that happens in these fields there is a clear retractions and etc. so there is a lot of the way we do is that we try to somehow cure these diseases in a preclinical model and in these papers and in these cells and when you ask this question why is that and there is a company that lost a lot of money on a clinical trial that just failed and when this company's money the clinical trial failed in this dementia field people wrote to them saying you know we knew that this won't work we knew that this target is not a right target why did you go with it and so the company asked like why didn't you tell us why didn't you tell us that it didn't work today we have paper journals that allow only positive storytelling there is only if you tell if you go to a journal and say this didn't work there is absolutely no place to do this and that's that and we all in my lab if you walk into my lab there is at least 90% of the data that talks only about negative and replicatory and kind of experimental and not storytelling worthy but there is this top 10% that is like kind of a story worthy or sensationalizing the way we cure diseases in the preclinical model that gets published and if you're an Alexander Fleming today if you are whoever you are making these amazing discoveries if you are in a rural part in let's say Africa or India or Asia somewhere and you make these brilliant discoveries today you couldn't you have to tell a story you would have to if Fleming's discovery were to be published today then it wouldn't be because you have you need to tell what the molecule is the identity of the molecule much later there is even in life sciences you need to tell the mechanism through which this observation happens in this case the fact that penicillin would work against bacteria through cell wall synthesis happened only 40 years later and today publishers demand that you tell a story behind these observations so as a result science is closed it is you see it is easy for me as a researcher to blame publishers saying those are the people who close science I also want to tell you not only that there is a demand for storytelling in science but there is also a desire from a researcher perspective to tell a story so if I make this observation like Alexander Fleming did I want to keep that story close because I want that observation close because I want to make sure I can collect all these elements of a sensational story that will go to a nature or a science I found that science matters few years ago and then whenever we talk about it they often ask if you publish that first piece the novelty for the rest of that story is gone can I still publish in nature and I think this is extremely important to understand that closeness in science the fact that we keep science close for a very long time from making discovery to publishing or dissemination of science comes from both both publishers as well as researchers and the reason is that we have this desire as well as the demand for storytelling we have to have all these elements and the elements cannot be negative they cannot they cannot contain plot spoilers I can't tell today that this work in the cell line in the transonic mouse this is the phenomena that works for Alzheimer's disease however when I change this model to another mutation another thing another just a cohort if it doesn't work I can't say this because I will be shooting myself in the foot right nobody is going to but that's what irreproducibility in terms of when I go to a clinical trial the fact that it doesn't work in different human beings could also be the reason that it doesn't work in this different clinical models and I said so a few years ago actually in already in 2009 I started to think quite a bit about really on as to why as human as scientists we have this desire and why do we do things that we are not really comfortable doing but we have to do and the storytelling for me came up as one of the strongest points that defines why we do things that the way we do and probably a cause for irreproducibility so we started to say perhaps what we need is some kind of a Lego like like kind of an instagrammage but in a way that you build these narrative as you go as opposed to tell the narrative from the beginning because you are biased as a as a researcher as an editor as a reviewer and so we created science matters without a need for story but just put these single observations and hypothesis they will be there should be periods you have published saved extended and the interesting thing with real time publishing and these elements that you would have to do is really that there is no reason to prune the narrative there is no reason to cut the narrative in order to tell the very cogent and a convincing and a positive story but all these elements can be part of this and not only that you could extend your narrative in your real time but at the same time this can also attach it as a result and narrative emerges naturally as opposed to an author pruned version of the science that we are being told today and so exactly three years ago today on the fifth of November 2000 oh it's not 2018 it's 2015 we launched Science Matters today is also my mom's birthday so I want to say and so today I will also talk about Eureka Blockchain that's the blockchain aspect of observation publishing and reviewing and rating and so we created Science Matters to do this where you could you could basically write up in it's like an Instagram post so to say and then it's sent to peer review we use triple blind peer review because there is huge amount of bias in peer reviewing and then it gets reviewed and rated and it gets published in an open access manner just by default open access and so one could as I said you can collaboratively attach all these elements that belong to the narrative and now what happens is that you can see now one could look at what is if we could qualify these edges the way that these nodes are connected whether this is an extending edge it just extends or it is a contradictory edge or a confirmatory edge now we can do something even cleverer we could say we can now make a reproducibility matrix for example to say which nodes are highly reproducible which nodes are not reproducible the left side could be an Alexander Fleming network or a double helix of a DNA network that is very reproducible but for some reason something is not reproducible it could be technical or it could be a biological or a scientific reason why this is not reproducible now we can confidently attach some score to these things and so we call it metric and this is the pattern that we applied for and now we filed both in the US in the EU now just the last couple of minutes I want to say with science matters we really attack this problem of storytelling in science allowing researchers to tell the story as they make these discoveries and as a result we can address both this design and the demand in storytelling for storytelling in science and we could publish these elements together however there are still some of these problems that we don't address and I thought and I thought that we could there is still this long delay in publishing research even though a single observation and we definitely reduce it to a sizable number however there is still this long delay going from a eureka moment of the moment of discovery to even putting them together there is some delay and there is a centralized trust that we talk about that the authors manipulate or like the authors control this data there is a centralized control by authors, reviewers, editors and the publishers and the other thing is there is this absence of fair credit you know we do a lot of these reviewing work and editing work for almost no money and now one could think about using crypto economy or tokenization model one could think about providing some fair credit and so we decided to use blockchain as in the parallel mode we have science matters up and running and it is there for three years and but at the same time we thought we should do an experiment with blockchain based publishing and trying to figure out can we address these other problems that we haven't addressed using blockchain based solution and this is called eureka it's eureka token.io you can have a look at it and in this way we could really immediately time stamp discoveries and that's why we call eureka so as soon as there is a robustly validated observation or a finding or a hypothesis or a retired professor immediately you could time stamp and then the other aspects of the scholarly process including evaluation of both observations as well as preprints and we can work assignment and then we could also call these research through involving funding agencies at the end one could by using tokenomics one could also incentivize replication we could also incentivize people's research that got cited instead of just having as a reference we also reward research that gets cited and then at the end we could also do data analytics of all of these data not the 10% the top 10% storytelling now if you allow researchers to publish negative contradictory confirmatory observation that's like tons of data which we anyways have we don't have to do this we anyways have it and this is something this would allow us to have much better analytics on the data that we that belongs to the narrative and so this is roughly the idea that one could use blockchain in most of these cases in most of the we use both off chain on chain aspects to to carry out the research cycle all the way from electronic lab notebooks to data analytics so I thought I could do you want to help me a little bit just to show me the prototype I want to show you the prototype and then so instead of doing an ICO and then asking for money and then do a writing just the white paper we thought we'll just pull our resources and start to create because we have science matters already start to create a prototype that would be useful for both researchers as well as if you are in the publishing industry one could use this to yeah go ahead there's no sound but it's just a minute that's fine great so you could start this is metamask you could you could log in and you write your own article then it gets hashed identifier and then it immediately goes to an editor the editor invites reviewers this is a functioning prototype that we have at the moment and the reviewer provides the review on the what you see is what you get templates so there's no reason to send out as an email or print out and etc you could do this we want to fully utilize the digitalization technology that we have available this is what it is you can write a review long side and then you could either annotate we use junior researchers we apply junior researchers to annotate but at the same time also I have senior researchers to provide big picture reviews and both of them and so you get rewarded in and instantly you get reward and that's the beauty of this peer-to-peer system in terms of fully utilizing this P2P transaction of anything that has research value and that's pretty much pretty much it is thank you I still thank you I still need to thank my team so if you don't mind so that's the these are I showed you already these are the token flow in the system and it's there are several advisors and both for Eureka as well as Science Matters and Science Matters is a team of me as well as Thomas who got the Nobel Prize a few years ago from Stanford and he and I created this platform in terms of the functioning protocol and the team behind Eureka is Thomas Bocek who created the P2P network he is a professor at the University of Zurich and now at the highest level and a fantastic team of researchers in Switzerland where Lukas Peloni is the developer and severant and on the editorial side we have Jan Lothal who is the editor-in-chief of the content management we have Isabel, Andrew, Tamara TJ and several others in the team and we have pretty good support from universities as well as now the Swiss National Science Foundation we are having discussions whether we could use this for even research data management finally this is my end I grew up in Islam in India I want to tell you this I grew up without electricity today I'm here and the reason is I had free access to opportunities I had free access to education it is immoral to put barriers between humans and knowledge be it for access or to create knowledge thank you thank you very much Loi are there any question comments thank you for your burden presentation my question is how is this token reward system working actually what is a participant rewarded for and how does this token which as I see is more or less symbolic is transforming to some kind of real-world monetary value so the token in terms of reward it happens at several levels one is that if you are a reviewer today you don't get any pay you don't get any money from the publishers or anybody who asked to review so immediately you get as soon as you provide a valid review you immediately get some of these tokens as a reward at the same time if you are an author and you published a paper that gets reproduced by somebody whether they reproduce it in a confirmatory or a contradictory way that again gets rewarded but as soon as your paper gets replicated these authors who replicate your paper get rewarded whether they say it negative or positive because we need all of this data so we don't punish but if the paper gets positively replicated then the original author also gets some of these tokens because that's we want to incentivize anything that can be replicated but we don't want to punish or penalize the author whose research cannot be replicated because we think punishing is not a good means to to incentivize de-incentivize the third thing is that if you are an author and your paper gets cited you get rewarded so these are the token systems and the token ecosystem and if you are a funder you also get you can fund through tokens if you are a grant administrator you can fund through some of these tokens so you can buy Eureka tokens and you can give it to your grantee do these tokens trade on the market what's their value or are they just nice little badges for owner the idea at the moment is not really to have a market value but at some point it will be in the exchange so initially you want to make an internal market of scientific that's exactly the ecosystem is built in Eureka we create an ecosystem that would be helpful for the researcher so that the $10 billion that we use for just publisher or $25 billion it goes back to research that's our goal we get into the crypto economy for Zines tomorrow and Zines publishing and I'm very excited about both sure is there one more quick comment question yes how do you build narratives with your system that's a great question so as soon as the nodes in the network become something like 7 or 8 an arbitrary number that contains extensions replications then we invite all these authors everyone contributed to what we call as matters narratives this is the separate section which is more of a review and I think every journal should be more of a review journal when there is a narrative where the single elements are reviewed and rated without the story context and only then we could assign validity to the scientific data as opposed to getting biased because of the narrative so matters narratives does not exist at the moment but if you could see this is in the pipeline as soon as we have these elements let's say each node is extended to 7 or 8 containing all these elements we will have matters and we think storytelling is a part of science science matters logo is stories can wait science can't so we don't say stories don't matter stories can wait so that science takes the priority great thank you very much so we have two more 20 minutes talks before we go to the third party and at this point I want to thank the sponsors that made the event happen and made it possible first of all is digital designs and then ETH Zurich it's not Ethereum Zurich it's mainly the library Zurich and the molecule project we will hear about the molecule project tomorrow and the other sponsors that are listed on this now we get into the space we talked about decentralization of science Yalda will talk about decentralization of space development okay so it's yours hello okay great hi I'm Yalda I studied mechanical engineering whenever I was in college about 10 years ago and I ended up working in product management for 10 years after that and I decided to change my path to get into the space sector so I took some night classes for astronautical engineering I thought it wasn't a lead applying for a masters program but it led and said towards creating a company first called space cooperative and our mission was to create so people can crowd source and crowd fund space missions and five months after we incorporate our business there was an article written by a futurist Julia Prisco and he proposed a decentralized space agency which was very similar to what we wanted to do but it talked about how you can create this ecosystem by creating a decentralized autonomous organization so we reached out to him and we decided to merge our visions and then that's how we started to lead towards this more utilizing blockchain to execute on our vision a lot of times when I talk to people about what we're working on they always say why focus on space when there are so many problems we need to solve on earth first and these are some of the reasons that I talk about sometimes it's like okay well climate change if it wasn't for space technology we wouldn't have some of these insulating technologies that we use on buildings all over earth if it wasn't for trying to develop these space missions and have that protection from this harsh space environment or space is such an inspirational thing that it is something that can bring humanity together to focus on something as a unified species so there's also that and then just like the drive to understand the universe more to explore that curiosity that's just in our human nature so it's like we can't just shut that off from us so that's why I'm focusing on space and also the movie 2001 a space Odyssey also really inspired me so yeah what is Space Decentral you know we aim to reinvigorate the push for space exploration with global citizens in control essentially we want to create an international space agency so it will be decentralized because no single corporation or nation will be responsible for its management it's autonomous because like the members that are part of the network they will control you know how work is directed how decisions are made and also which projects to fund and then it's a space agency because the goal is to really come up with a strategic space plan a space program not just to always select random ideas but to actually build a roadmap that accelerates our timeline into becoming a space bearing civilization with the ultimate goal it's like you know it's about expansion expansion of knowledge expansion of humanity throughout the cosmos and you know expansion of just being a collective as a human species so in this talk I'm going to talk a little bit about aerospace crowd history just kind of like the history of crowd funding and crowdsourcing in aerospace one example will be X-Prize and then I'll talk about kind of the trajectory towards the X-Prize type model into the Space Decentral model and then I'm going to talk about phase one of how Space Decentral currently works right now and then phase two of how it will ideally work so aerospace crowd history so you can probably say the starting point of crowd sourcing in aerospace might have been the Deutsche Prize in the 1900s and that was for you know the challenge was to you know build an airship that goes from this airfield in France to the Eiffel Tower in back so it was about 11 kilometers round trip and yeah that was awarded to a Brazilian and he won $100,000 for that and then there are a few other prizes from the 1900s until the 1990s like the Ortiz Prize but some of the ones that you probably have heard about recently are the X-Prize and the first X-Prize was also space related and that was $10 million for the first non-governmental organization to launch a reusable manned spacecraft and that was awarded in 2004 and then the recent one that we've all probably heard about is the Lunar X-Prize and teams have been working on that for about 11 years and they recently just canceled it this year since no one was able to launch their landers in time but what did happen as far as those X-Prize teams go is even though the prize was $30 million over $300 million of funding went towards these different groups that were developing these lunar lander technologies or rovers or what have you so some of the top examples are SpaceIL and they were the Israeli group, a non-profit even though they were a non-profit they were still able to get $95 million worth of contribution some from the founders of the team philanthropists, a little bit from the Israeli space agency iSpace, they're a Japanese company they actually just recently got so this year or like the large amount of it was this year and then Moon Express they've had about 65 million I think they just recently closed a pretty large round so I guess if you think about the incentive structure here SpaceIL is an interesting example because they were a non-profit there were only 30 paid members working on the team but 200 volunteers for 10 years without any pay at all so a lot of the drive for that was to work on something challenging inspire people and I think that's kind of what is great about SpaceIL is it brings people together to accomplish the impossible and it's not always about the financial reward but the financial reward can still be a nice motivating factor but it's not an ultimate requirement and then as far as crowdfunding goes in SpaceIL from the micro-citizen level some of the projects you probably heard about are ARCID and that was Planetary Resources crowdfunding project and that was like your prize would be you'd get a selfie of yourself in the backdrop of SpaceIL but they actually ended up giving back people's money for that because even though the crowdfunding campaign was successful they still didn't have much external funding to fully execute on it and then there was the light sale by Planetary Resources I believe that they launched that first mission but it didn't end up working out well but they're planning a light sale too right now and then a recent one was just for like a telescope so yeah now I want to talk more about how we go from the X Prize to something like SpaceD Central so right now in SpaceD Central we actually announced an open source lunar program in July and since then people have been working on the space mission in a very open manner we have weekly meetings on Mondays people we have weekly meetings on Mondays everything's like in an open Google Drive and GitHub everything's like transparently organized it's not really on the blockchain yet but I'm going to talk more about Phase 2 and how it will progress to that but essentially the objective is to demonstrate in situ resource utilization technology or ISRU to 3D print on the moon surface using lunar regolith or like the moon dust as feedstock so you wouldn't send anything else to print but you'd mine the local resources to eventually start off with printing a brick and then after subsequent missions you can eventually print a habitat and that can ultimately reduce the costs of space travel if you can do ISRU on the moon so yeah this is our flagship mission and whenever we ask some of the people that are part of the team now like what motivated you to join some answers were make friends with like-minded people or just like space a chance to participate in something new or to be an asset to society and then a few other answers where you know more space specific advancing interesting lunar projects or interested in space resource utilization so it's like a broad area of interest as far as why people are participating in this project and yeah right now like I said we launched we announced this mission in July and there's about like 20 people that are actively contributing to the project you know a lot from America, Canada India, Australia, Sweden the UK, Brazil as far as like people's heritage goes and we want to keep growing the network and it's actually like we haven't really focused that much on the publicity and growing more team members for this because the problem is if you want to like grow it from like 20 to 100 like the skill you need you need like project managers you need people that are gonna be very diligent about like the task management like leading groups so that's just kind of trying to hash out throughout this process if you really want to scale you need you need to be better at task management you need to be better at project management and you need people on the team that want to do those skills because a lot of people are actually interested in more individual contributor level like doing the actual like okay like research or design because it's like kind of a side project and like doing project management on the side isn't always that fascinating for people so how does it initially work? So right now we have a Space Decentral Network SpaceDecentral.net for collaboration it's a centralized social network it's not on the blockchain yet eventually it will be a decentralized application but for now it's more of a forum to track the different projects and it has like an integration with Google Drive and then like I said before we're using GitHub for project management so yeah we're kind of laying down the different tasks and we're also going through a process of kind of starting to estimate the relative value of one task to another as far as like how long it will take to complete it because that is what will ultimately go into the phase two which is properly attributing work where it was done but this is like some of the recent work of the network is doing a trade study to decide the manufacturing method like whether it's going to be microwave sintering, solar sintering there are different additive manufacturing methods and the group is going through trade studies to determine the best one and then also there's room for people that aren't scientists or engineers too we had a task on GitHub it was just like design a logo and then these are some of the designs we got we're leaning towards something that looks like the last one right now we're iterating on that so how does it ideally work so this is how a space agency works as far as NASA goes you have pre-phase A concept studies and then there are all these like design reviews and you know concept phase A technology development phase B all the way up to phase F when you're closing out the mission so there are all of these milestones in between and there are a lot of processes as well so if we want to create this decentralized network you need to design the system that it can at least support maybe a slightly leaner version of this but you know you would have different experts that would be matched to the different review cycles you would have different conditions that need to occur before you know funding is opened up or before a concept is selected but that's just kind of like a high level overview but it's like how are we going to do this you know we're going to have the Ethereum blockchain at the lower level as far as tracking the value of the money that will be flowing through the ecosystem or the contributions of each person we're going to be using Aragon for governance and it's also a decentralized application framework because if you're a decentralized autonomous organization that means governance and decision making is the core of what you're doing but Aragon will support the voting on which projects to fund or even voting on if you want to create a technical council electing that technical council deciding when you might want to dissolve that technical council so just because you're a decentralized autonomous organization doesn't mean it's always going to be completely flat but it means that as a collective you can decide when you want hierarchy and when you want to get rid of it as well and that's similar to how worker owned as well and then Space Decentral that will be more of a focus on the scientific or distributed engineering tools so for the work that we do on Aragon those will be more generic applications that any DAO can use but then the Space Decentral ones will be how we can further build upon it to support the scientific and engineering community okay so I think about six more minutes I'll try to quickly go through this but the Space Decentral DAO will be a two token ecosystem so one is FTL or faster than light and that's the transferable token that can be purchased and it can be staked for governance rights and it's also used to prioritize the higher level program so a token-weighted vote on if the network should focus on Mars, Moon, Earth so you got essentially a distribution and that higher level vote essentially determines how many SDN you mint per program each year so if the vote said we should do 70% Mars, 20% Moon, 10% Earth that's kind of what your supply of SDN will be and you'll do these votes usually on a yearly basis or whatever the network thinks makes sense as far as being able to make progress on the space program but SDN it's minted by the DAO and you can see fit and it's awarded to intellectual contributors so essentially there will be SDN on every task and if you complete a task you collect SDN so you can start to just see who are the top contributors in the network it's decoupled from the one that can be purchased because that gives the network more flexibility to do interesting things and then similarly what you can do is since FTL is the one that has value on the side, on a cyclical basis we're going to distribute rewards to the contributors so you can think of this as an evolution to the XPRIZE model where instead of $30 million at the end of the year after you do this goal you can do things more like maybe on a yearly basis you distribute $5 million to everyone that's active in the network so that's how we think we can evolve this model and how if you create something like the XPRIZE again having like 50 teams compete against each other maybe there's a way you can do it that encourages collaboration so you could have actually sent that lander to the moon because there are so many intelligent teams working on it maybe with this new way where there is a better way to track everyone's work you can share the prize but at the end of the day you saw that the money that was put into those projects far away from what the prizes were anyhow so right now we have a space mission activation process where people can come up with different proposals to be selected for crowdsourcing so essentially there's a curation process before a project is fully activated on the network so you know you can post an idea, start to discuss informed teams, draft the proposal get feedback and review and then it'll be filtered to make sure that it fits into the model, it's open source etc and then in parallel people are developing Space Essential like they're working on the coral mission or they're helping with the tools they're collecting these SDN and that gives them a voting share to actually participate in the process to select one of the proposals so these are kind of the two parallel ways that people can contribute it's like if you have an idea you go through the first track of proposing missions but if you just want to contribute to some of the active missions already you can contribute to those and then that will give you a stake to vote so this is essentially the mission activation vote if you had a selected mission you also get SDN for that and then what happens is just because your mission was selected doesn't mean you and your team are going to be the only ones working on it as part of submitting this proposal to the network you're submitting it to be an open source project so as a collective dow there will be more of a detailed project plan developed with tasks and then people from the network can start to work on it and then how is FTL awarded essentially it kind of goes through a process where you have these tasks, they have SDN allocated to them a contributor completes the task and then eventually whenever a reward cycle occurs they get FTL in proportion to how much SDN they collected so right now what we're working on is developing a suite of applications for Aragon and we're calling it that planning suite but essentially these are the different tools that the dow will be using to allocate funding and make decisions and any other organization that wants to also do similar types of crowd sourcing and crowdfunding can use these apps and you don't have nothing to do with our token you can have your own two token ecosystem to build your network if you want to employ similar processes so this is what we're kind of giving back to the community and how we think applications should be developed in general as far as like if you want to develop an application for a dow you don't have to tie it to your token to develop these common tools together so all organizations that want to operate in a decentralized manner will eventually have a fully fledged enterprise suite so here's an example of the tokenized task management system I mean it's much more detail how it works but people can estimate bounties and then you can get approval from the entire organization to actually fund it and then this is kind of like the rewards ecosystem where you can create a new word a new cycle, a map which token it's allocated to and you know how much that allocation is yeah so it's unknown what the future holds but it's up to us to shape it that's spacey central thank you very much yalla thank you very much yeah I mean how many people are in space right now in space? yeah just three right? if they have to lend it's the first time since like 30 years there are no humans in low air orbit it's kind of sad so we are in a time of space depression sort of yeah well I mean there's all these new space transportation companies yeah this is new things do you think when will they be like be able to like launch humans in America again you mean now using the Soyuz? I'm not sure I'm sorry I haven't been following every space news few more years right? we have to come up with new ideas to bring humans into space make it much cheaper because it's really hard to get off the gravity the earth if you would live on moon it would be like like 3% of the energy necessary to go to moon orbit it's because it's an exponential function right? so when you are working on this I was on a conference last year and there was a guy who said let's ICO the Mars mission how much would every human on earth has to contribute to bring us to Mars it's like a few dollars right? and we could like spend maybe 100 and other people that don't have so much money just like a few cents yeah yeah I mean this is excitement right? so are there any other comments or questions? just one like who likes space? going to space yeah okay cool see we already have like a few people for the ICO okay? I bet the others would be too they are just tired to raise their hand okay so and I want to thank a few people like Brother Tillman and Iona for like helping me with the check-in and I want to thank the great live streaming team Cyber Academy again and I want to I want to thank CIO and CODOA for helping with the presentation and also the logistics involved in this field okay thank you very much and I'm excited to announce the last talk so well we talked about blockchain and immutable data trail data models like look at data constrain the access to data and we know how blockchain sort of works like there are like notes that evaluate all the transactions that happened on the blockchain like in Bitcoin for example yeah but what if the notes not only evaluate like things on the blockchain but off chain things or actually the knowledge that was created and James works on this vision it's a living knowledge network it's a moonshot project a very cool project he starts low and then like for sake of time he will present another time you can like check out James presentations online they are worth seeing it for sure and but we need to like have a mathematical description of knowledge to make this possible right have you ever thought about a mathematical description of knowledge huh Miliza and now Bartmos will explain us how mathematical description of knowledge works in my own microphone working yeah there we go cool maybe at this beginning maybe you can open it not like in the middle no worries always when we're doing live you gotta have all these technical things and so on just hit that for me alright well first what I'd like to do though actually is I'd like to thank this man right here everyone give him a round of applause no no no no no I love this guy thank you I'm willing to give up a few minutes of my time for that tell us about knowledge okay well okay so you know yeah I'm here I'm a mathematician I think sometimes I'm also an AI researcher for a very large corporation which I'm not going to promote because I'm not here for that but apparently somehow but my mom's really proud of that she doesn't know what I do but it sounds important so what I want to talk about here is a mathematical theory of knowledge now I'm releasing a paper now part one where we define knowledge mathematically this is not a philosophy or something like that this is a little bit different so you know you're gonna have to really sit down for the math here I'm sorry for that but I'm Bart Maul St. Clair and I do something called the amateur academic where I try to promote open science and academics for everyone and that's what I'm really here trying to do and I really love doing that you can of course always find me on Facebook, Twitter, Quora, LinkedIn even ResearchGate it's all available there please like and subscribe I do this for the love I do this to promote open science knowledge and you know it's quite ironic that I actually mathematically try to come up with definitions of knowledge when I try to promote it like this so into a mathematical theory of knowledge part one it's a part of a three part series and releasing that now if you're watching this on YouTube on my channel then you can click on the link below if you're here there's no link I don't know what you're gonna click on so I have three choices how to present this this is like really difficult to even do and presenting it in a very short period of time you know that's really difficult so what are my three choices here I can describe it with math of course I could try it without math that's a maybe and I could talk about the applications which you know honestly people love the applications of things they love practical things they love examples so you know I'm just gonna skip that and go right into the applications maybe that's easier and it will motivate you guys to care about this so of course in machine learning what you can do of course is for typing machine learning algorithms and combining them if you have a mathematical theory of knowledge it's very helpful for that knowledge extraction obviously knowledge extraction and of course even possibly new methods so that's what I'm really excited about and that's why I do this really abstract mathematics the other thing you could do with this is of course in expert systems you can improve the modeling of expert systems of course you can create new logics and you can even combine different types of machine learning and expert systems to try to build hybrid systems that are much better so those are the practical motivations and you can of course put this on the blockchain if you like I mean we're at a blockchain talk so I'll throw in those words every now and again like blockchain or maybe internet of things so we're now at the crossroads here do I do it mathematically or not and you know if it's a mathematical theory of knowledge I actually do need to hit you with math I hope you don't fall asleep during this I think they would kill me for this so why don't we split the difference why don't we do some math just a light version okay you know if you clicked on this and you're watching this you don't know what you were thinking because it's a mathematical theory of knowledge not a philosophical theory of knowledge so bear with it here so first off we have the first axiom here in words knowledge is a compression of informational observations what the heck does that mean first off let's define information we have this guy he defines information as an abstract so a question that seems good and there's no math there yet we got two slides in and we're no math so but here we go so an information algebra is what he does and I'm very glad he did this so I didn't have to thank you for that Professor Kolas so an information algebra is a pair of satisfying axioms 1 through 9 which I don't put here because that would take way too long so I don't put those axioms in but you can find them easily and that's from like I said Kolas and that's our foundation of information when I talk about information I'm not talking about facts a lot of people think facts or information technology it's not what it means it means something else this is another type of information so let's get into this here you see there's like a cursive D here so there's some special type of D represents domains of abstract questions now what the heck is that so D is a distributive lattice and I've underlined this here because I'm going to be going to lattices all the time I love order theory things like that so we're going to be talking about lattices a lot so unfortunately that's why actually it's a cursive D sorry I didn't use LaTeX for this presentation I didn't want to go too full math for you guys but it looks prettier in LaTeX that's for sure the D here is cursive because it's a lattice so let's just talk about lattice this is important and I don't want to do this to you but it's important so if you look it says important on the slide so it's actually important a lattice has two basic things okay it's an order it's a partially ordered set you see the normal L here and you have some sort of inclusion it could be greater than less than equal to that kind of thing you know or it could be it precedes or includes but you know you can go with a greater than less than if you want that works fine and secondly there are operators for meet and join the heck is meet and join well you got a great like diagram here so a lattice has operators for meet and join if you notice there's for meet it's actually pointing down so it's the infimum it's going down to try to meet two members of a set it's trying to go down and find out where they meet the infimum and you have also join which is pointing in the other direction it's going up and when it's going up you got a supremum so that's really all you need to know where things go up and they meet and you need to know that basically that's a lattice more or less so now things are getting serious let me take off my jacket here this is getting serious here we go so now back to that so D is a distributive lattice good we've got that now everyone's still with me you're still awake yeah okay great just checking so alright we have phi here and it represents a set of pieces of information where each piece where you see that that's a little phi relates to a specific domain in our lattice of domains D okay so this is this is from Professor Kola so this is not I wish I would have come up with all this myself I didn't do that I wish I could take credit so that's what information is here it's relating to domains alright so and you have phi here it's a semi group which you know I don't know if you need to know what that is maybe not it's good to know but I wrote that down here on the slide you can read that that's good so now this is important because it's under combination there's several operations you can do an information algebra and combination is one of them I'm not gonna get into that okay I'm gonna spare you it's gonna be okay we're gonna get through this together so knowledge representation non-dependent the next action what does that mean medium dependent well it means there are knowledge types surprise surprise there's deterministic and non-deterministic and we're gonna be discussing those types of knowledge okay so let's go for the non-deterministic that's the Shannon information entropy is a good example of that maybe some of you know that maybe not but it is it's surprise okay it's surprise where you didn't know I was gonna do that and if it was a probabilistic thing you would see that if you don't know what's gonna be predicted in a system next of signals such as with Morse code or something then you know the Shannon entropy is higher because you're getting new information and that's Shannon information entropy that was a very bad example but it's funny you're still there I guess right okay yeah okay so deterministic now let's talk about deterministic okay so information content is one of the important things there and that's order remember we're talking about the lattice we're talking about ordering and the next one of course is vagueness you know you've ever heard of vague information or vague data where things aren't very precise that can happen right now it would be really cool if we could combine Boolean and non-Boolean set theories meaning you know one that's very precise and one that's very vague people have been doing this a lot but a lot of it wasn't very very good and there are very technical reasons for that and we're gonna talk about that right here so what are the predicates of set logic or set theory and that's membership and equality membership of course element of equality so if it's planetary right so when you get into fuzzy sets you have fuzzy membership where it's defined on a closed unit interval usually something like that and it's a function that's a mapping there to the closed unit interval or to a lattice as we talked about before lattice and still regular quality though not fuzzy equality and there was a lot of problems with that because if you only take one of the predicates of set theory and fuzzify it it breaks things it's not very good I'm not gonna get into why so there's these guys he first suggested it and mbar Michael Barr who actually did this and they came up with this thing which I call fuzzy I know that's because it's funny because it gives you fuzzy equality and so I call it fuzzy sets they don't do that I do that hopefully that sticks and yeah these guys did a really great job with this I highly recommend this paper especially if you're into category theory it's really good so just really briefly I'm gonna show this you don't have to understand what this is but you can see here that there's a two projection mappings to a set X here and they'll actually they're morphisms in the same category I don't know if that means anything to you guys but that's what that is and so you have one mapping for your membership and one for your quality okay so that's that's really great now why is that cool well it forms a complete lattice remember that lattice okay hopefully and the cool thing about this is you can do power sets and function sets and you can do everything of an intuitionistic logic so that's really really great and this was proven by Michael Barr shout out to that guy he's amazing that guy did some really good he's still alive by the way 81 years old so with these fuzzy sets you can do boolean, non-boolean you can do fuzzy information they form a topos which is really great so it's a complete hatings algebra that's great for some reasons which I'm not gonna explain so that's really cool okay that's that's one of the foundations of these types of knowledge okay I I hope you're still with me on this so the cool thing though is with fuzzy lattice type embeddings so I put a meme in here so just because they said that would be funny is it no okay okay so you can do lattice embeddings here for different types of fuzzy sets so you can produce all of them that's really great so type 2 of course is the measures well in this case we're gonna talk strictly about probability but it's measure-theoretic in general and under R the real numbers it does not form a complete lattice unlike the other type and of course you have information content and entropy now of course information is very important information is handled discreetly it's handled finitely it's countable whereas knowledge maybe not so that's the difference here and that's actually another thing why in the case where you have R for the real numbers or something like that it doesn't form a complete lattice so you can't have an order-theoretic description really that's complete and it does not actually form an information algebra according to colas because it has to be a distributive and complete lattice and you don't get that and the reason behind all this is very very very complicated but maybe you've heard of the Banach-Tarski paradox where you can if you have uncountable sets you can rearrange them in a way that you think you would actually get a sphere that's now two spheres and when you're trying to measure stuff like volume or something like that these measures become meaningless then and so that's actually why the guys who invented probability formally you know with sigma algebras and this kind of difficult stuff to explain right here they did this they limited this so that you could actually get meaningful measures out of these things and that's why otherwise you can get into some really bad problems here and that's why it doesn't form a complete lattice and I wrote a proof on this it's actually pretty straightforward it's in the paper all the stuff has been proven you can check it out or you can just come up to me and ask me to write it down really quickly for you or something so going back to it though knowledge is a compression of informational observations what do we mean by compression what do we mean by compression well that's using these types of knowledge using type one and type two isomorphic with each other sometimes you can have cases where they're equivalent and in some cases they're not in some cases one is better in some cases you can use both of them and you can combine them and you're always trying to find what you would call the atomic algebra something that's the least representation that you need which would be compression which this is something we're going to be talking about in part two of the paper I'm not going to do that to you now I think this was enough for you guys I hope like I said this time I decided to go really really technical and I'm sorry for that but damn it it's a mathematical theory of knowledge deal with it I do the amateur academic you can always check me out on Facebook Twitter, Quora, even LinkedIn whatever I'm always available you can ask me questions especially on Quora I love to answer questions of Quora and so that's what I do what I'd like to do right now really quickly is thank all of my friends my loved ones all of them G's out there all you guys watching I know you guys are streaming this right now probably my mom thanks mom thank you so much for all of your love and support over the years so that I can do this crazy math stuff and thanks to that big company that pays me to do AI stuff so I can do this kind of crazy stuff with you guys it's all about the love and I hope really that this inspires people to be more academic and research because I think honestly that when it comes to things like fake news you don't need to build a machine learning algorithm you need to build people who can actually figure things out better and that happens through academics and teaching academic methods and if there's only one thing you walk away from besides what a lattice is here it would be that so that was a mathematical theory of knowledge part one defining knowledge thank you very much for your time thank you thank you very much cool so knowledge is a compression of data right no no this kind of we describe like bring an observation together describe it as a form of compression isn't it so we got this cool so thank you very much and we are going I do have any comments questions like really quick quick quick no okay because you all know now what okay so you can ask Bartmoss at the party which will be across the lobby at the backstage area there will be music, there will be drinks there is one hour of open bar and I'm just telling you this because there will be another one after this but you should take advantage of the first hour without knowing that there will be a second hour and I'm telling you this here because nobody of the hotel is here good okay so and there will be food and tomorrow will be at 830 there will be the open mic session so if you come up with some crazy stupid ideas where you have some alcohol and you put it down on your napkin and tomorrow you will still have some alcohol then you can present the project it's not a good idea then you don't do it okay but I mean the best ideas come up when you are not yourself right because then you are think beyond the perceived and like established tracks right I had when I thought about shoot all this blockchain stuff will have some applications and signs I had a hangover yeah when I like first saw the time about it yeah seriously okay this has something together right it has something okay so enough talking 830 there will be the napkin and open mic session and the people from the hackathon will present and then at 930 will like have publishing and peer review on the blockchain get down to earth get down to work do serious stuff and then the very interesting stuff the crypto economy we will have a lawyer we will have Paul from the molecule project talking and then will come up like what needs to be done to like get blockchain for signs up and running what should we do like how do we build the open science ecosystem prevent silos walled gardens and everything and we can like shape the field right now okay so thank you very much for everything and see you at the third party yeah thank you