 You're an independent research organization here in Vietnam, and you've been very active in the project, and you've worked in the economics field. From a scientific perspective, what do you think are the greatest challenges, or why are you here today? So, we are working on the gel-equipped economics, and we have been working in a setting publishing for quite some time. We decided and started the Gel for Research Cultures by looking into how specific cultures existed in research, and how researchers are building their own culture of knowledge, how they actually interact with specific data, how tools actually get into existence in these kind of communities. This is very interesting if you look at the blockchain space, the crypto space, because they have a lot of opinionated data, also opinion-led research happening, because for most of the research is actually happening on company levels. So there's not so many true scientific foundations that we have compared to any other scientific discipline, and since crypto-economics is not an existing discipline, we have to, in a way, as researchers, look at defined fields as such. As we have it now, crypto-economics is a very ethereum-led space, I would say. Also, if you consider it invented and it started a lot of this, also the crypto-economics is beyond ethereum, so we're trying to look at it with a changeable perspective of economics. So, for example, also, how can we criticize certain elements of specific new incentivations that have come through in the system, by redefining the system of being a token economics, possibly also questioning a few of these metrics. Okay, that's very interesting. However, that's very specific. Yeah, it's very specific. But it's always very specific to research in crypto-economics. This, however, is how blockchain and crypto-economics can be useful to us to help the scientific, public, and community in general. So, not only crypto-economics research, so at which potentials do you see coming blockchain at IE for research in general? So, in general, we have a problem in academic publishing that is a lot of, in a way, close communication, like close to the projects that we have there. So, what we, in my opinion, have is the problem that a lot of research has to be paid for somewhat in the end to the possibility of blockchain to connect and take away its power to additional publishing institutions more to, for example, democratize in a way a scientific publication as such to go through this problem. Here we view elements, like we can assume open access aspects that are not existing. If you look at it now, if you look at the publishing, it's actually working in Sweden. A few stakeholders are controlling it. In the end, even if we look at open access, all these institutional research to be published, there's a lot of interesting approaches to this. Not necessarily, but only these projects that are a lot more distorted, like distracted and not being selfless through blockchain because we are so difficult to raise how we can actually now integrate with data to make sure that it's consistent so that we can make sure that open access is controlled and very powerful. So we can use protection to have a certain pathological use of blockchain to see and identify some of the things that work here. So in the case of object and object information that works here, we can actually make sure that it's consistent and all the people are going to understand what's so interesting. Yes. It's actually also possibly to control the network Okay, great. Do you have to take the case on your own? Yes. Exactly. The only thing that unfortunately doesn't work is the lag. Okay. Yes. Okay. Yes, that too. I hope that's in order and then we can do it live. Unfortunately. But that's the only way to do it. Yes, but if you record it you won't be able to say, yes, great. I'll come back later. Good. Thank you. It's a little bit loud. Yes, it's really loud. It's a little bit loud. It's a little bit loud. Okay. Thank you. Thank you. Thank you. Okay. Yes, but I think it's a little bit loud. It's a little bit loud. You can't record it. So it's Yeah, we have to get these components out of the code, because that is the only way to do it. That's what it looks like, too, doesn't it? That's all right, it's that way. Yeah, it's that way, it's that way. Too much. Yeah, it's that way. That's it. It's that way, it's that way. Yeah, it's that way. Yeah. Oh, well, let's go. Let's go. Let's go. Let's go. Let's go. Let's go. Hello? Uh, so we have to take that thing Um, um, um, um, um, um, um, um, um, um, um, Good morning everyone, we are very happy to welcome you here at this first scientific publishing on the blockchain conference or on conference rather as we would like to see it and we're very happy to work together with Surke Batling from blockchain for science who has come from Berlin to conduct this conference with us. This is the first in a series of conferences and it's a twin conference because a lot of you or some of you will be continuing this trip to Zurich and there will be a two-day conference. So without further ado I will be speaking a bit more later. Alfred Taudes who is our director of the scientific lead of the Research Institute for Cryptoachemomics wants to say a few words to you. One welcome from my side, welcome at this nice campus. I hope you are enjoying your time, at least we have very nice weather. If anybody of you is interested in a special tour of the campus please contact me and I should be sure to give you some break or so if you have any questions please contact me. I hope you will have a very good time and I think you are in a very important mission and I'm glad that you are okay because in simple words our current scientific publishing system is fucked up. I'm glad that I also have a number of people who also see that this needs some change. Change usually is not a single peak crowd. It starts by some motivated people and I'm very glad that these motivated people are here. So that's such a good time. Thank you. A few words so I'm very happy that you are all here and the way we designed this arm conference so as a blockchain world lives from participation and peer-to-peer things we hope after getting used to each other we will like open up and discuss stuff and at any time I would say like if you would like to bring up a topic or discuss a topic I think you can just speak up or if you want to introduce some stuff later on its first structure and then it becomes more unstructured and then hopefully more structured again. And housekeeping wise I think you all have Wi-Fi working. The live stream is not working. We are recording and taking pictures if anybody of you is not okay with it let me know. And I think that's all. Best for the presentation is to use the drop off links on the web page and that's all from my side and we start with Professor Pichler. So we would very much like to welcome Professor Pichler here who is not only a bit select of the portion but him and his team are also part of the research institute for crypto economics so please welcome him. So everybody on behalf of the director of the youth they have the honor to welcome all of you to this arm conference in scientific publishing on the blockchain and honestly I had to Google the word arm conference. Professor for banking and finance not so much in this blockchain and in technology things. So learn what an arm conference is and I think it's a good idea to have it in this more unstructured and open way. And then I recognize that I have to provide an opening keynote so I thought it's a public keynote or a private keynote. I'm not sure but I can promise you that whatever note I will give is a more unstructured one. And try to let's say summarize my thoughts as a professor of finance with a let's say lose link to blockchain technology and as a vice rector of research of a university. Yeah so first of all I think that that's clear all of you are here because of that that this is a very promising field of research. I think blockchain and crypto economics in general is for sure one of the fastest growing but maybe also one of the most rapidly changing fields in research in economics and business in broad sense and will be for the forthcoming years at least. But I also think that to grow fast and to be exposed to rapid changes is clearly also a challenge but this makes this specific research field also extremely interesting. And second this specific topic has first a huge potential to influence the way how research is organized from an institutional perspective. So it's an interesting feedback group. It's a let's say like a regular conference and research topic but the contents of the research itself has a huge potential to influence the way of how we're doing research in the future. And I can also talk a little bit from my perspective as a vice rector for research because of this function responsible for the library and the library services of this university. And this is one of the very special duties at least once a year I get a staple of forms where I have to sign the money transfers to the publishing houses. And it's always big money. But in a sense what I feel that we will have to talk about that in the afternoon that we are in very complex and strategic situations at universities vis-à-vis the publishing firms. And I try to look at it as an economic aid with a very bad strategic situation at least currently. And why? And in a nutshell the situation is the following. So the research content is of course produced by researchers as we are and we are paid by our universities. Quality control of the production process so that the medium is done by researchers who are paid by universities. So that having this production exercise as an example the raw material and the refinement effort is provided by universities. And finally the universities are paying millions of billions to buy the final products which are more or less produced by themselves. So one may ask why this can happen and obviously there is a let's say first part of the answer that is that the publishers are offering a technology for the processing of submissions, processing of reviews and also for the final publication. This is one element. The other element is that the big publishing houses have built a big reputational value for their respective journals. And given the current technology this building of reputation can only sustain in an holistic structure in Culebro. And a little bit explain that, what I mean. So there are entrance barriers for outsiders into this market and these entrance barriers seem to be extremely high. And many open access journal initiatives have experienced that the publishing, that the technology to publish something on the internet is the less tricky part. It's the reputation part which is the essential one. So the key element I think in this unpleasant strategic situation of universities is the combination of reputational value. The publishing houses have created and the technology that they are providing. And the processing technology that they are providing is a centralized one. So the reputation of the publishers is combined with a centralized processing technology because of trust. Nobody would submit the journal to a reviewing process which is not trustable. And nobody would publish a paper out of the reviewing process that is not trustable. So this technology combined with the effort to build reputation is always sufficient to cost. And this creates the entrance barrier and this creates this oligopoly. So from my personal point of view, the decentralized ledger technology as blockchain has definitely the potential to make the use of decentralized technology no longer necessary. So if blockchain works and has the technology to replace decentralized technology of the publishers, then the entrance cost would dramatically decrease. And this will lead to a fundamental change of the payoffs in this matrix of this economic name between the publishers and universities. And this is clearly, I think, to be disruptive. If you have an equilibrium based on an economic game and the game is determined by the payoffs in the payoff matrix and you change the payoffs dramatically, you will have different equilibrium. So this is maybe a historical chance to have a transition from one system to the other. And I think maybe some of the presentations that you will be able to dig deeper into this question. I think, of course, it's a question of how the technology works, whether the new technologies trustable or sufficiently trustable to replace decentralized solutions. And I think even the situation that, at least in Europe, there is a lot of new negotiations with the big publishing houses. There is a political support by the European Union together with more dependence from the publishing houses as a university system. Maybe this is a once-in-a-lifetime chance to participate in a new and maybe very promising development. So to come to an end, I wish all of us many interesting and stimulating presentations, many fruitful discussions. And maybe, despite, of course, the tight conference schedule, some relaxing hours here at the campus in Vienna. I'm up next and my talk will be on the state of crypto-economic research in general. And parts of this state of the research will be relevant to this conference today. And I'm very happy, Christian, to see someone from Ethereum here today in Vienna. I think we're on the right track. And crypto-economics really is a very or relatively new scientific field of research. And as most people, people who don't come from computer science or engineering background, they would think it's a new line of economics. It really isn't. Before we talk about the state of crypto-economics research, we need to know what is crypto-economics and does that work? So crypto-economics is not really a subject of economics. Could you, in another tab, open this side? At least, traditionally, it comes out of applied topography that takes into account economic incentives and economic theory. So traditionally, crypto-economics has been in the computer science departments, very specialized computer science departments, and economists have less worked on that field, even though there have been conferences and places where this theory has merged a little bit. And if we look at Bitcoin, Ethereum and everything that followed, there are really products of crypto-economics. It's applied crypto-economics. However, that science is quite a new one. It's very important to understand, and I think everyone here in the room probably, or most people here, already understand that Bitcoin is not a currency, but it is this crypto-economic operating system for a new type of economy. And at the same time, it's a payment supplementary, and at the same time the token as itself is a new type of asset class. And this new crypto-economics operating system allows us to move from a world that is organized like this, top-down with organizations that have one legal entity, and where the agents within these organizations or stakeholders are organized by legal contracts. Crypto-economics allows distributed autonomous stakeholders that are distributed globally in various jurisdictions, allows these autonomous stakeholders to work as a distributed network. There is no centralized legal entity. There is no employment or delivery contract or whatever contract in any way, shape or form. The only contract there is is in the protocol, which is transparent and auto-enforceable, even when the conditions are met. And crypto-economics is a combination of cryptography, peer-to-peer network theory, peer-to-peer networks, and game theory. And it's important because crypto-economics has to make sure that a distributed network of actors that do not know and trust each other can interact in a way that is truthful and where the network is, where it's really, really, really expensive or almost impossible to attack the network. So last summer, this is just some old numbers from last summer. It costs around, in order to conduct a 51% attack on Bitcoin, it would have cost you 1.8 billion in hardware and 3.4 million in electricity per day to be able to attack that network. And so, yes, it is possible to manipulate the network that is run without the centralized entity, but it's really expensive and that is the result of crypto-economics. So I'm telling this story in a very condensed way because most of us already know it. So after Bitcoin, we had Ethereum and Ethereum allowed us to, all of a sudden, create our own kind of currencies or tokens and crypto-economic networks on top, like application networks, decentralized networks with the application token on top of Ethereum. And last year alone, well, we had $4 billion in the worth of cryptocurrencies that were raised for ICOs. The problem is that the crypto-economics of native blockchain tokens, and we will get into that a bit later, is well-defined, proof of work behind Bitcoin, Ethereum, and many other chains, and we're now moving into alternative crypto-economic systems or consensus protocols. The problem is that on an application token level for usage utility tokens, etc., where it's not an asset-backed token, the design functions are not really defined yet. And we've had $4 billion raised for tokens last year, most of which, or a lot of which, are application tokens with really lousy mechanism design, because nobody knows what they're doing, and that might flag fire quite soon. So what is classic crypto-economics research? As we're speaking, these words and terms are being defined. So from how I see it, you could classify three types of research areas on a very high level. One is the consensus protocols of native blockchain tokens, a group of work, a group of stake, and everything else that is following right now. On the other hand, you have the token engineering of application tokens, and this is now becoming a thing. We are seeing more and more people discussing online about mechanism design of application tokens that are attack-resistant, because most of them have no mechanism design, as I said. Most of the tokens that have been issued for ICOs were probably a pretense just to conduct an ICO, but they don't really have a meaningful mechanism design behind them. Or very often, people mistake putting old-world assets, representing them in a token, and putting, like, kind of shifting the token from A to B, but there is no automated mechanism behind many of these tokens that really allows us to interact in a distributed way. That's very abstract, so let's look at an example that would be relevant for what we're doing here. If in the scientific publishing process, we want to move away from peer-to-peer publishing to swarm review, where we don't have centralized entities with two peer reviewers like quality controlling our academic research, and if we would like to decentralize this more, we would need some decentralized reputation systems, but we need to design these decentralized reputation systems in a way that they're non-manipulative, that they're attack-resistant, and that is very much dependent on mechanism design, and this is a new field of research on an application layer. And the third research area is probably somewhere in between this and this. I see it as a kind of middleware, anything kind of the design of state channels, for example, that allow us to solve some, for example, scalability issues of the underlying blockchain protocols. They also need to be designed, have a pre-economic design behind them, so that is a field of research. This is all very high-level, so if I had an hour, we could go more in detail. But if we look at crypto or economics as a new kind of, or relatively new size that is now being extended into non-traditional fields, you have traditional cryptography, which is the line of research, and there is a lot happening there. State-of-the-art blockchains are based on a certain type of cryptography, but newer blockchains are used in different types of cryptography that are allowing us to have, for example, more anonymous transactions or choose whether we want to have more anonymous transactions, like multi-party computations, zero-knowledge proofs, et cetera. On the other hand, we have the field of economics, our economic incentives that interact with this. So, we're moving slowly, possibly moving away from proof of work to alternative consensus mechanisms, proof of state, et cetera, but these alternative consensus mechanisms haven't been tested yet in many cases, and we're all very much looking forward to how the CASPA transition will happen in Ethereum. On the other hand, one big line of research is anything related to governance, because today we talk about crypto-economics because it's the economics incentive that allow us to have this distributed network of actors kind of auto-enforced rules in an attack-resistant way, but in the end, a blockchain or similar systems are governance tools that allow us to have automated governance or more agile forms of governance or geographically distributed forms of governance. Therefore, we have this whole area of research that touches anything from legal aspects, government aspects, public policy aspects, and there is a lot of knowledge out there because we're not really reinventing the wheel. Blockchain and crypto-economics is a kind of new technology, and we have to merge the know-how of regulatory governance, legal and public policy environments and merge this with the knowledge of creating these new systems, so we don't have problems that, for example, a lot of blockchains are having right now around hard-fork discussions and who decides over a code upgrade. So is it rule of code or do we have governance, often governance tools, and if yes, how do we want to design them? So here we need to work together with public policy and legal experts because there is a lot of know-how. And then on the application layer, it's just a word here, but really blockchain applications or decentralized applications will have a very different logic to them than centralized applications we know today for two main reasons because we're reinventing the data structure. Data is public to everyone in the future in the decentralized web. That means that one single entity cannot monopolize data. Hopefully we will have more privacy through multi-part of computations and zero-knowledge proof kind of solutions while being able to conduct complex applications that use AI. But at the same time, the second part, obviously, is that auto-enforcable smart contracts reduce transaction costs and get rid of the middleman, and we have more transparency. So the field of research that stands from here is very big. And I think in 2018, 2017 was probably the year of the ICOs. 2018 might be the year where we see more tokenizing real assets on one hand, governments or companies tokenizing assets of the real world and moving into that space. But I think that 2018 might also be the year where we talk much more about mechanism design, token engineering, what is a token, and how do I design a system that's truly distributed. And we have too little know-how and we need to, on an applied level and on a research level, talk much more about it. This is why we created the Foshen Institute for Crypto-Economy. There are crypto-economics lab here at the Vienna University of Economics. We started beginning of this year and we have already 30 researchers from various disciplines. I couldn't put it all in a slide so you only have the headlines from... Oh, that's a screenshot now. So we have from the computer science department's researchers, from the legal department's researchers, we have from our economics department's finance department, but also from the business department's researchers, all trying to wrap their head around the implications and also the core research that needs to be conducted. And one of the biggest problems that we're facing now is that all these different researchers coming from different fields all have their own set of vocabulary. And most of the time we spend, like when a legal scholar talks about a contract, they mean a very different thing than when a computer scientist talks about a contract or a smart contract. So definitions is a big challenge. But I think one of the second big challenge is also that on an application level we have a lot of researchers that already understand that this is disruption, but our greatest challenge is to make the cryptographers and the computer scientists work together with the economists and the econometricians. Because most economists and econometricians do not understand that their know-how is very useful for mechanism design and token engineering. And so I think we will need some time to get everyone up to speed and hopefully truly really work, create this great body of work. And I'm doing this together with Alphataldis, and I hope that next time this year we will be able to present more. Currently we're working on the ideas to have a research map of research questions. Our greatest challenge is to define the research questions. That are relevant in the different fields. So if you want to know what we're doing and stay up to date, follow us on social media. And other than that, I hope that this will be a very fruitful and we will have a second conference next year. And I'll hand over to the next speaker. Is there any questions? Sorry. It's an unconscious. So today will be more the talk part and tomorrow will probably be a little bit more, definitely more interactive part, but if there are any questions. Click one. Are you aware of other things going wrong around in the world? Like you, building up the department here to be honest or something else going on somewhere else? We've really researched it in that extent and in that size I believe we are the first. But there are like many universities worldwide have some kind of blockchain lab or crypto lab. It's usually one-dimensional. It's a business center for example in Frankfurt. There is however a small interdisciplinary institution at RMIT in Melbourne. They've been conducting legal scholars that have been working with economists, but there are like four or five people. I think in the size and in the scope there are a few researchers interdisciplinary. We're the first. There may be what I didn't say, but some of you know is Alfa Taubes has been the initiator of the Austrian Blockchain Center that we just submitted for which will be a research cluster. Riot will be part of it too like a lot of independent and institutional research institutions in Austria will be working together in an even more interdisciplinary fashion. And if we get the funding, which we will know end of the year, we will have a full-fledged research cluster out of Austria. And I think we are in that sense really the first. I didn't notice, but do you have anthropologists involved? No, unfortunately, not yet. We would like to. So we only just started. We would like to... The BU in itself is a business and economics university, but because of its size it has many different departments. I think what we still lack are the social science departments. I think we can learn a lot from biology, biomimicry, anthropology, obviously. We would like to start collaborating with the complexity hub there here because this is super complexity science. And I think what we also need to understand is that probably AI is a huge... There is a huge interrelation between machine learning, AI and blockchain. And... Yes. It will be a step-by-step process. So ideally we want to do it more interdisciplinary than now. The greatest challenge right now is that blockchain has been a technology that has been driven by the industry, by the real world, let's say. It has built on a body of work, of cryptography, peer-to-peer networks and game theory of decades of academic research, but it was really driven out of the real world. And what I find here is that academia there is this huge time lag. They don't know what's going on and they are slowly reading up. Some of it's not true for everyone, but even in the computer science departments not everyone was up to speed. We will need a bit more time. But then I think we can leverage the potential of academic research as they have a lot of time. And their aim is to research for the sake of research. And right now these are very research-intense technologies. So if we are able to bridge that gap I think it will be very important. Economics is strongly tied to money. You mentioned the European systems asset crisis. But for knowledge and science we've got far broader currency perspective than what we mean by reputation. Is it truthful? So I was wondering if your research was going to expand beyond the monetary corner in the economics? Yes, hopefully. So reputation systems as you said is a very important aspect. So really the research that we're conducting here my role is together with Alfa Taudes is to coordinate the research of these researchers. All of these 30 researchers are not working for us. They are independent researchers the head of institutes like for example Stefa Bichler or Hanne-Norwe. Are you still here? Hanne-Norwe was also working with Stefa Bichler. There are independent researchers who are working at their own institutes here but we're trying to coordinate the research efforts and to be this point where some interdisciplinary conversation and dialogue can happen. So we cannot tell the researchers what to research. We can rather inspire them and provide a platform for idea exchange within the institutions but also with the outside world. So I'm happy for any type of input on how to improve this and there is a lot of know-how we don't have at the BU because we're not the social sciences university, unfortunately. I would say that you've done basically well to get through the people in the University of Auckland and aside, no this is not my own research that I refuse to engage. It's right that you're doing. We were surprised ourselves. I think that when we started last summer to plan this research institute we were like hand-selecting who to and why. And then once it became because it wasn't public yet. Once it became public, they started to flaunt us. It's the first design of the RMI team and they tried to have people involved but they said it was nobody to publish so that doesn't matter. Maybe the specific way the research institutes hear the interdisciplinary research institutes at the BU work, they're like a virtual institute. We got some base funding for me and a second person who will work for me for five years but we're not, as I said, a top-down institution and I don't know what we did. But I think it's a very interesting field so everybody knows it's a thing. I'm sure it was also a timing thing. Had we started a year earlier we probably would have gotten much less interest from the researchers. It was perfect timing. It was already out there in the media so even maybe leaders, scholars who are not really into technology and new things realize that it is a thing. How do you see funding coming from to run the outcome in the future? We are seeing a lot of interest from companies. They are trying to wrap their head around how they can apply it. Unfortunately, companies are on an application level. However, for this research cluster we've got a lot of letter of intent from many crypto startups also because they're, for example, the Ocean Protocol or the Glucis people are designing their own token but they don't know what the mechanism design should be so we have a lot of interest to work together with econometricians here. The problem is that they have money post-ICO. The only problem is that there is time lag still so we're trying to bridge this gap. There is a lot of money coming from the industry. I don't know. We're not official yet. It's very likely, but not finalized. My personal research area is blockchain and sustainability. How to incentivize a sustainable world and we might get a 200k funding from the Austrian Development Agency. I think it's a thing now if people are giving money for those kind of things. Maybe we should wrap it up because I'm overtime and I'll be here the whole day. I can go over to David. Can you introduce yourself? You just met two weeks ago in London and I'm very excited that you speak here. It's been a long time since I've done a talk like this on a better sort of socratic dialogue and conferences. Thank you to Senki for inviting me to give maybe a historical perspective. My main crime is that I'm very old. I thought rather than introduce myself I'll introduce myself and my background in this through the slide. If anyone wants to interrupt me I really don't like the sound of my own voice so I'll answer that. This is where I started. I was a researcher and immunologist. You see a degree in evolutionary genetics and immunology and also a medical student at the Sharon Cross Hospital. I spent nine years doing medicine there. I was coming up to my finals and I wanted to be a research immunologist. But I was a troubled young man and so I also took four years out to do philosophy and that's when I came across a strategic problem that what I was doing was illegal. You're not allowed to run your philosophy degree at the same time as you're doing a medical degree and my finals were plashing so I had to ask for another year out and I came up with an idea to do this interdisciplinary student note taking system for medical students. A way of attaching your patient histories to the subjects we were taught in all these different departments. This was in 1989 and because it was going to be difficult for me to take a year out I had really good references and stuff so I went to Imperial College and I went and talked to the computer department there and they showed me a couple of papers in this very early system, and it's one I read like Van Waal Bush's As We May Think and the foundation and if anyone hasn't read that paper that was 1945 his description of what science should be and how knowledge should be shared is completely seminal in real paper, in other words it was in the newspaper rather than at the computer and that's what I decided I wanted to do so I got first of all the sabbatical and then I founded this multimedia authoring centre which was actually my first attempt at marketing so Mac, I wanted sponsorship from Apple any case by the way this isn't what the hospital looked like I couldn't find a good picture of this hospital and this hospital, the most interesting thing about this hospital is its architecture so it's called Charon Cross and the architects design this hospital as a cross like this is a cross if you look at it vertically there's all the patients in these rooms here overlooking the graveyard so this is a metaphor for me about complex systems design and architecture the architect was concentrating on something his job should have been to think about this the researchers were in this building the hospitals but they didn't look at the systemic effects as what that felt like as a patient in these rooms sitting a bed overlooking a graveyard any case during this period I basically created a wiki in 1990 this was not online then it was a desktop application and it was linked to students and myself we created about 14,000 pages and we linked there was a really beautiful system where as you were typing them out you would just highlight a phrase a term you didn't understand click enter and then you could create a dictionary page and that would link to all the other similar pages and other disciplines and it was linked to 100,000 images at that time it was a laser disk so as soon as you went to that page if you look up the database you would have this the problem I had in this time because I had, the dean gave me a department, a virtual department it was a physical department I don't know where it was but it was an abusive room and we had no funding it was at the time of UK being the poor man of Europe and Margaret Thatcher and funding being withdrawn from the universities and so forth in London but I had to try and get funding and it was withdrawn from companies and the main academic criticism I had is when the professors came to the research department and I showed them all this kind of whizzing stuff because I had equipment from Philips and Apple and all that sort of stuff but it's kind of students who made this how do we know that we can safely pass on this information to other people, how can we test it so I started to think about that and I developed basically some of the things into that software one was basically a page-rank algorithm it was basically I wanted to say you as a student endorse this page and someone else endorses you so I can assign a reputation of quality to this particular thing and I was very much looking at with publishers how we could publish this information so the second thing I added to it was something called publishing points multiple contributions of all these authors so bear in mind this is 1991 roundabout then what are the lessons I learnt from this first of all don't believe lawyers that's really really important I love law by the way when I started to talk about the publishing points the lawyer saying that's illegal you can't do a currency only governments can do that please stop which I did for about five years the politics of the institution was really important as well the nature of the technology is interdisciplinary and you know it's fantastic you've got this interdisciplinary department together but that is so hard to do because of all the structural incentives built into departments departments would not collaborate and I made a fundamental mistake in my career of instead of choosing the best department and put myself underneath it I said I had to bring these departments together and so I had no no support in that sense and the other lesson is some things take a very long time this is a bit of a cut I'll actually go here so I submitted two papers there an MIT Trinity College one was on this peer review system that I was really passionate about and the other was theater and VR and high-end graphics because the companies were approaching us to show us off and they accepted this paper as a keynote and not the academic one which I was really interested in I think they wanted the flash video protector that was the main thing they wanted kind of a whizzy thing and then I got lots of people wanting to invest and I've been working for three years without money in science basically and these people gave me an office and we started to basically take shows and do art and interactive performances that's how I saw the educational platform that we should build there was a teacher fielding questions with a projection and pointing at things and that's very much like what we could do in a performance space at that time but I'm not going to go too much because I'm bringing this stuff and out of that came the next time that I looked at reputation which was I started something we're together with 12 people we come north of course in Sweden and Psyche John Doniston in America called Liquid Democracy in about for me this was 2002 I think we basically worked on it the three of us came together in Sweden I can't remember based too much around about 2003 to 2006 and Liquid Democracy is basically although it's been taken up in specific ways it's basically for me at least it's the science of reputation fields and how you can use them to add value to the collective decision making whether that be electing an MP or a scientific post or a peer review panel or a particular invention the reason I called it Liquid Democracy is because I've now been funded in art because no one else have funded me and I've started this thing called the multi well it was a commission that's only in comparison with multicultural yoghurt I did more science in this project than I did in medicine by the way we were studying how you could create multicultural yoghurt from the different bacteria strains and see whether they could co-inhabit peacefully in one yoghurt strain and we created this political party and this company to manufacture multicultural yoghurt and I had to figure out what the political system for that party was so I called it Liquid Democracy taking these reputation metrics from the science stuff so revisiting Liquid Democracy I left Liquid Democracy around 2006 to 2009 because I became very aware and this is a current issue to do with blockchain and it probably will be for another couple of years I reckon is that it's very much individuals in an enormous political or you know I call it kind of Uber for science or something like this you know or Uber for individuals working within a network and the core thing and now there's been some interesting papers that illustrate this as well is real collective intelligence comes out small group work so the missing thing in Liquid Democracy for me was how do we create these small group work so I started to work on this thing called Liquid Law which is a domain specific legal language which you could constitute these groups and give them real real robustness and then worked on several science projects SoMatch was one for EPSRC project interdisciplinary again trying to look at how companies research departments could share knowledge and that was difficult interestingly because I found it easier in art and in computer science to share knowledge and when I came back to science it was so competitive and so difficult researchers were refusing to share their current knowledge at conferences and I found that is really interesting if science is worse at sharing knowledge than artists that's the same thing I got involved in Ethereum in December 2013 and through 2014 because as soon as I heard that you could do interesting things with the programmatic space in blockchain but in Bitcoin when Ethereum came up I thought that's the language that we can create these government structures these reputation systems and so forth and a lot of money is going to be invested in that and that enables us to do things that scale the arm to do with money but to do with all sorts of other values and I've been working with Walt Cunningham, who's the inventor of the post-wiki on this writing platform which is very much about how, if I write it's basically a micro publishing platform without the blockchain so if I write a small page you can fork it and then you can customize it make it yourself and then someone else can fork it and then you can use the blockchain server and these ideas start flowing through a network of servers carrying the provenance and the history of every single change edit and authorship as it goes but it's not robust, it's just in a Node.js project so we've done two experiments with that to do with that protocol and to do with IPFS and also to do with Holochain which is a post blockchain project over the last two years so how much time I've got this is something that I started four or five years ago which is basically looking at in science if you look sociologically and anthropologically at knowledge generation in science everything is emphasized on novel research, new research if you're not doing something new you get no brownie points, citation index and that aspect of anthropologically speaking of knowledge generation is probably only about 10% or 15% of the real value of knowledge patient and another hugely important aspect is your ability as a thinker, as a researcher to spot the quality of someone else's work and it's very interesting that the sort of person who is very good at sort of forging ahead and a very dedicated piece of research and coming up with something novel is a completely different emotional and intellectual personality someone who's very good with the group and saying that was really interesting what you said and what you said and we could put these things together they're not the same mindset they're not the same quality and that is basically what peer reviewers should be doing so that area of how you incentivize and accredit that sort of sphere is what made an index that comes from tipping point Malcolm Gladwell's idea of a particular character who moves across different disciplines understands and picks them up and synthesizes them into something new and this is something that I'm particularly interested in working on this year oh yeah, we know about peer review stuff and this is what I would like and this is one of the reasons I'm here is it feels like there is a possibility now of bringing these things together around an open science core so there's lots of money lots of startups and a lot of the reason all this stuff didn't happen since 1994 or 5 onwards is because of the economic and social incentives of the institutions out there not finding any value in the interdisciplinary nature of research so at this point of time the marriage of universities the finance that's out there in blockchain and so forth indicates that we could establish an open science protocol in the center in which companies can come and benefit from and yet the evolution of the process, the mechanism and the incentives and the knowledge that it's published in science is done in a better way than it's ever been possible to do before and it's only if we collaborate rather than getting in our own departmental silos and saying those guys are doing it before me and we work out the governance of that collaboration that we'll be able to do this so this is the cool thing that I wouldn't really go I'm a new form of scientific journal other people are working on this and I'm really hoping that I'll find some sort of collaboration on that I want to work on micro-publications very small, published early published often but keep your accreditation semantic addressable content addressable links things like IPFS so those links last 100 years they don't get broken this is just super obvious stuff I mean I've known the IPFS guys since they've been wandering around the world in four or five years and they're steadily working on this and they're super smart and it's hard work and there are other ways of doing it but that's the sort of thing science should be doing and everyone in science should know this immutable provenance that means I need to be secure which is something that I just thought of in the last two days I need to be secure if Matthias forks it and someone else forks it that if in three years time my work is used there is a provable link to what I said and I can use it on my CV and that's what blockchain is really good for data and simulations and bringing that in you've got to also be aware of the things that hit in the browser you've got to be aware of web assembly tool chains, web components standard based stuff in order to think how can we bring data and how can we bring simulations which is the core of complex science work is arguing over a simulation how can we bring that into the publishing process so yeah, making it robust so this I'm going to quickly maybe show a couple of things we're not hard set on this sort of stuff but in case people don't know or the sort of tools that are coming out at the moment a bit left-wing this is a democracy earth democracy earth foundation a couple of years ago it's liquid democracy contracts on the ethereum blockchain so we're hoping to use this and marry it not to democratic decision making but science publishing this is super important so this is self-sovereign identity there are a bunch of projects in this area this should be linked to all kids and similar sorts of things to give robust identity to people publishing whether they be citizen sciences or academics and getting that right is core to the text so we're looking at choosing this the best one that we can this year at least and then these are the sort of things which I don't hear there's probably lots of people in this room working on it but in my childhood I don't hear too many people talking about it so forking is a really interesting political and scientific concept so in terms of collaborative writing I've been now working I've written 30,000 odd pages in hypermedia landscapes with other people and when you have a practice of how you write and research this you start writing in a different way and to be free and feel comfortable that someone takes an early stage idea forks it changes it into something you disagree with is deeply uncomfortable for scientists or even business people but if we can succeed in incentivising that we'll do a fundamental thing for human knowledge generation so understanding what fog is and how we can use it in the publishing process is key argument maps are how you feedback argument maps are used in AI research they're used in political science as far as I can see but getting the visualisation I've worked on it a lot to do with liquid democracy getting that feedback right and the soft incentives and the hard incentives of representing someone's argument versus someone else's argument where do they meet where do they agree where do they disagree how can I disagree with this particular point while I agree with the rest and if this particular point changes I'm sure that discussion or that small group that's a cool thing getting the sociology the interface design and adding the maths behind it knowledge roles different knowledge roles are important we're not all the same we don't all think the same how do we put these different knowledge roles together and make sure they're all incentivised not just one elite group that as the gentleman said is fucking up science for the last 50 years algorithms and architecture so algorithms like when I was working on the liquid democracy algorithms at Chairman Cross Hospital in 1990 I didn't even know it was an algorithm I must have worked through 20 different forms of process and code of how this reputation stuff worked for me it was just pragmatic how do you how do you organise a series of steps so that you get the desirable outcome and that and code algorithm though is now almost like this pre-slike term if you've published an algorithm you've done something amazing they're like the new lawyers the new venerated people but these are so powerful and so important that we need to demystify them and put them under human governments and human control we need to bring in all these disciplines into that research area so that we make sure that our future technology science, AI algorithm design is something that doesn't just travel off into intellectual space and leave the rest of humanity wondering what's happening this is two projects that I'm working on at the moment it's hard to clean this is basically a due diligence research platform for sustainable investment in clean tech so we basically need to create a platform that allows people to investigate the science of say a new battery design or a new wind farm also the financial investment aspects and make rational decisions about what to invest the reason I like this project is because it's got a nice business model people want to invest they want to make good investment decisions and yet all the science can be published purely open so we can get investment on this, we can build a platform and yet everything we do is open for sustainability for the environment so there's a board of rich people who've got some money they want to put their investment into and this is an early stage project there are probably other projects out there and again teamwork is what this is about I've got some software that I could show in terms of the publishing stuff but I think I'm out of time so I'm not going to do that the last thing I want to say the other project we're working on is two academic conferences so one on economics and anthropology, January 2019 and we want to organize a decentralized conference happening at different locations so we've got three universities at the moment and three continents also involving civil society and we want to publish that in a robust way as possible so we don't want to do another world social forum occupied type action we want to combine social conversation with robust new form of academic publishing using these techniques so I'm really hoping to join up or link up with people working on static site generation content addressable links blockchain based provenance in a new form of journal and exploring different forms of peer review in that area and really try and get the word out there by working together to do a conference and that conference would be jointly owned by all the participants so the governance of that conference is important it's not my conference it's not this university's conference it's decentralized globally governed conference where we use the decentralized tools and work together to publish it in an annual experiment so working on one of that in environmental science which will be in two years, 18 months time and generally in 2019 we're working on one in economics and politics which we're calling DAVOS which is basically going to be a fringe event of DAVOS in Switzerland DAVOS in Portuguese means to give voice so we're loading it to the Montpeixero Foundation we're working with University of São Paulo use London Metropolitan University in London and a couple of some are in Africa which isn't confirmed yet London Metropolitan University just said yeah yeah we'll definitely do it but nothing signed yet and we want to invite people and universities to self-organize their own events and publish in a new way and I think it's only by coming together and working together to do something together that we will address these interdisciplinary problems you can show the software maybe tomorrow that would be a good opportunity and something to ask or to like mention so I really like your like view at these things and I summarize it in a way that you're saying that things that we are solving this blockchain today or like try to incorporate in this blockchain for science platforms have been there before like challenges before like reputation and continuous publication but this trusted third parties so it's a problem in the past to trust traditional trusted third parties like ResearchGate or Publisher Platform with these reputation systems right not really no we have news now okay okay yeah so for instance when I was working with John Donnerso working we can work together because he had VC invest them from Hamburg so we were open source but he wanted to publish all the digital signed votes to different news net channels if you do that to enough people it's effectively like publishing to a blockchain it's impossible to control news net channels so blockchain is amazing but it's main amazing is that it hypnotizes everyone with technology and money so people have ended up moving towards what they should have done years ago in any case it also does provide not just the incentives and magic but it also doesn't provide the most trusted trustless infrastructure that you can leverage a whole lot of other interesting stuff on top of so it's not bullshit it's really interesting important technology but the fact is we could have done most of what we need to do in science publishing without blockchain years ago excellent yeah yes so I have a question with the social conversation that you were mentioning it's kind of interesting because we were talking about how artists like to share more information than scientists do and I think that's quite interesting because if you go to a platform like state youtube people are just trying their best to share as much as content as possible and they're incentivized to do it so do you think that there is a halfway point where you can what do you think is missing in science that is present in all these art platforms or character platforms where the science is as much a creative process as in your piece so do you think there is something there the main thing is the pressure on scientists to publish first original work and the different metrics that have been increasingly applied to that so science like the BBC used to be basically a paternalistic institution you'd find someone good give them a space and leave them to do whatever they were going to do and they could then follow their own but with the increasing management engineering of science and metrics just like what happened to the BBC people came in with audience research and a lot of monitoring of what was happening this basically meant that you might want to collaborate with this person from an intellectual perspective but you then wouldn't get your paper out so you could do this so the main problem is the structure of the scientific institutions and the incentive systems in place and what's great about blockchain in this space is we have complete scope to re-engineer that and what I think would be great is if we create a new economic model for scientific publishing I think that's what everyone here is talking about and we look at how libraries can be involved in that we look at doing it at plus minus zero profit sort of basis and we make sure that we motivate and incentivize what scientists want to do if they want to work with someone who's in a different department or a different part of the world then we need to get not just the publishing industry out of the way we need to get the university incentives out of the way saying only here please and there are various other ones and we need to look at that and I think one of the core bodies to involve there are the scientific institutions these people are responsible for understanding the structure of science and in my opinion they're completely negative it's obvious you've been thinking about this for a long time so it's cool that decentralization was already a movement before blockchain came around and we explained that very well so I was you also did a good job of demystifying algorithms a little bit at least for me so you can feel good about that something I've encountered in I guess like the state of the research around crypto right now is that algorithms that people are coming up with on governance they're kind of fruit of mystery that might not be the right word for it but like Bitcoin and Ethereum they're worried about the economics and just the computer science of the protocol and a lot of people are trying to steer these projects in the direction of making the governance model more modular depending on different schools of thought and just different inputs before they make decisions so has there been any kind of movements that you've seen towards like a multidisciplinary governance model that can kind of work together all on one standard and then kind of crowd source an algorithm instead of one person getting all the credit for it like you I've been looking for that and trying to find people so the core project I'm actually working on is called platform.Earth and it was about creating a containerized, dockerized legal governance platform for the commons we were using, we were building on a project called oneclick.org which has real legal governance for COPs and voluntary not-for-profit associations and adding that to the blockchain but the idea is not to come up with what a lot of startups will be interested in is like a specific algorithm because that's where the money is we own that, we can patent it, we can copyright it we can do this and we can update our tokens on it but to say this is just minimal and within that you can add all sorts of algorithms and governance structures, you can fork it you can run your own in scientific publishing so we want to put an academic journal at the heart of this governance and we want to say that's how the journal is governed this is how the money is transparent this is how the incentives are but people can then drag and drop metaphorically speaking their own peer review algorithms onto that and then you can have a flourishing of experimentation, some will produce good stuff and some won't, you can do longitudinal studies of this, we can actually do real science about science, think of that that would be amazing wouldn't it so instead of saying we can't create a baseline just to start with minimal viable governance as well and the other term that I like to use published, I don't like publishing stuff is common law algorithms so the design of an algorithm based on multi-stakeholder meetings using good facilitation, writing exploration of it, then coming up with a functional specification of what the algorithm should achieve and then designing it not people the clever mathematicians and coders and the business people coming up with an algorithm designed for their own particular well view and economic interest and then say everyone use this, it's great so common law algorithms and please if you've got any desire to collaborate, talk to each other come talk to me, let's do something together you built your open science ecosystem ok, thank you very much that was good Ingo, you want to go next? and I'm also one of the old people I realized because it was very active in use yet and I have a similar idea and intention like David but I decided to go another route so I was very active in the open data space and in the early open science space, even though I didn't know it was called open science and I thought we need to do something, we need to change the way how these things work and instead of going down the route to develop a platform or think more about it scientifically, I decided no, I need to go back a little bit more, I was presenting a project at a conference of publishers of way across publishers in Germany and I've seen other publishers and I realized it's not going to happen, anything fundamentally new with these publishers they are very well set in their roles it's just not going to happen we need to create our own publisher and this is why I found it with two other friends in Ringer and what I want to talk about now is why we need open science and why we need the blockchain to actually work I think it has to be mentioned many times we are in a disability crisis for example only of a set of 59 papers that were important in economics could be reproduced with the same data and help from the authors which for me it's completely crazy I mean you take the same data these people had you use the same analysis like these people had and they help you to do it correctly and you don't get the same result they publish that's something that should never happen that should never happen it's inverse in creating the cancer research only 11.5% out of 53 landmark studies could be replicated which obviously means that quite a bit of the cancer treatment we have is based on results that are not real results they may be noise or something else I don't know but this might explain why we still are not able to treat cancer the way we maybe should be able to treat it and I was working long time in neuroscience and it's an open truth that the media power is only 18% so a good friend of mine always used to say from our research like 90% is greatly over exaggerated completely noise 5% you can trust more or less and the other 5% you can really work with and that's not just based in these topics like neuroscience etc that's all around the world in science world like chemistry, biology, physics, medicine and other it's very common that you're not able to reproduce a result and there's nothing wrong with it maybe you have some external influence that changed your experiment that's actually to find out what's happening so if you're not able to reproduce a result there's something going on that's worth investigating and if you're able to reproduce a result that explains it then send it out and get other people to try to reproduce it that's an important part of science and actually when I was supervising students the first thing I put my students up, if I started in a topic was to reproduce some result, someone else has published and that if the manuscript reproduces it's great, if not we can look why not the main point was they get a feeling for the topic they need to work on and the second main point is actually that's very important for science to be able to state the reproductive result they're not able to reproduce it and this is a fundamental part of science that up till now is very very complicated it's almost impossible to publish and that should not be there should be a space in scientific publishing where I can publish preproductions so a quick question what's happening here and I'll tell you more about science as a system not the abstract science like we usually say okay science is you create a hypothesis and you look at the mountain of knowledge that has been created before you extract some hypothesis then you test the hypothesis and then you say okay it worked out, it didn't work out it worked out because of hypothesis that's not how it's done in the real world in the real world it looks more like this you have the university or some fungal who gives money to some big professor does the professor give space and money to something called regular stick and this postdoc then creates an experiment with the help of this big professor tests the hypothesis validates the hypothesis of course all this costs a little bit of money and as that costs money there are big incentives to speed up that project as that process very very fast and you start with an experiment and it's going to work out you create a hypothesis that you're sure it's going to work out and validation should be easy even though we're doing this way I would say that 90% of the results fail you get negative results and that's great, that's cool that's information, you learn something from negative results but the problem is you cannot publish negative results you can only publish positive results and 90% of research is wasted for the rest of the world apart from your department your department knows that can't even work out but the rest of the world doesn't know that so experiments are repeated around the world where you all know they're not going to work out why? that's the basis of research then important thing to publish it because publication gives the highly evaluated token back to the big professor who needs to report back to the university because the university funding depends on the impact factor so that's the real world at least in my impression working at academia for academia and one problem you have here is hacking, scientists are naturally born hackers so my rules for system security I also work as consultant for that is anything that can be hacked gets hacked all man-made systems can be hacked somewhere scientists are naturally born hackers because we hack nature we want to find out how nature is working so we need to hack nature we're born that way and if you want to make a system prove wrong that it's hacking you need to embrace the hackers but that's key yourself I mean bitcoin manage that bitcoin is said to be a way if you find a way how to hack bitcoin you actually use that way to make bitcoin stronger because you make money out of it you make bitcoin out of it when they realized how to do the mining, the hashing instead of a computer or a CPU they didn't use it to attack the bitcoin network they used it to mine faster to mine more bitcoins because they make money out of it that's what I say that's the genius level, that's embracing the hackers so if you look back at that system of science there are obviously lots of places where we can hack stuff I don't think that's complete there may be more ways for that that's the most obvious ones so you can hack your experiments you do some biased selection of results no one is going to notice because you are the one who does the kind of stuff hypothesis, you do some biased reasoning and it helps to get that through with the refusional validation p-value hacking and when it goes to publishing you suppress your negative results it's easy because you cannot publish them anyway so you only write in the positive results in your result publication, share your refus I send that to some editor and say hey editor could you please send that to the following refus which I will find out and then it goes through citation hacking years ago especially in medicine people started to hack citations just add a lot of citations to your article so the level of infant factor 4 in medical journals was rising rising up and now we are in a situation where I think the New England Journal of Medicine has an infant factor of 73 or 78 something that's crazy I mean that's totally crazy and that's overall citation hacking that's going on and I don't believe that we should put the blame on the people who do that the problem is that infant factor is completely bullshit to use just forget it, it may be a good idea to select why it's been created initially to select which subscription to hold in the library but it's completely bullshit to use infant factor to classify a researcher a research project so what can we do, what can we do to change it so our idea is to avoid the experiment selective bias use open science, open up your experiments open up your reasoning why did you do the experiment this way it doesn't need to be perfect but more transparency is going ahead the hypothesis created open discussion so people can say no I don't think that's the right way or it's a good idea but maybe do it this way and then discuss why you have the hypothesis this way and if people have different hypothesis they can take it and run with it I think that's what you said be open to the forking I have an idea, you can have a different idea maybe yours better we don't know, this is science the reason why we do science is to create knowledge and as long as there's an attribution because I want people to know that I was the first one to came up with the idea and someone else took it and changed it but there's still part of my idea in it it's fine for me validation if we can publish repetitions we can make sure that the experiment that worked out a thousand times worldwide is known to be very valid but if we can publish that it didn't work out 999 times we know it's probably some noise effect or something it's also going to be able to publish negative results obviously if I try something that doesn't work out I should publish it and maybe someone else here says ok I know Ingo is stupid he did that mistake here I believe if I change that it's going to work it's great take my data result one result if it works out great if it doesn't work out another thing that we learned in this way we can publish probably like 90% of science which is right now something like the dark matter of science there but no one can see it it can bring it to the light and people can work with it publication to work against J refus we need open refus obviously if someone doesn't like me and writes in bad refus he can still do it but at least his name will be on there and other people will read it and say ok why did you say that so it's his or her repetition it's going to be in danger if we open up the refus then obviously we need to get away with that something like open science is not going to do because we are not in a position to do it to generalize input factor is something that universities have to take away have to delete so so we we found with the publisher we said ok what can we do on the publisher side what we can do is actually create space for all these places like open science open discussion repetition open refus so we sat down and said let's make a lot of mega channels maybe it will be crazy but we just had the idea and we had one mega channel for open science where we say all areas of research are welcome the only thing that we ask you is follow the scientific methods because it's open science open up your analysis scripts open up your results then you can send it to us then you publish next one is we said we want to have a venue for discussion so we create a channel for open discussion and we also are evolving round the way so right now we have two submissions submissions in this thing cloud journal and turned out that an initial idea how to do it is not really any question so first we said thought we made first a refu process and then publication open access and publish the refus now we realize now it's going to be very complicated to refu these kind of articles someone proposes a new idea that's a combination of three different subjects it's very very hard to find a refu that has the same knowledge and I thought initially it's not going to be complicated to just take three different refus and they refu one part but the refus actually said no we don't want to do that so we now switch in here to an open publication process so first publish and then do the peer refu process afterwards and at first we will be finding with some very open peer refu or maybe not in refu something but here we have the problem that many universities always pay the publishing fee if it's peer refu so we need to have the peer refu still there we have one for a selection of petitions so you can publish something and this is an example where we expect lots of small stuff like saying I repeated that just like it's written in the article if you couldn't work properly you would try out new stuff we have one from H2 besides especially and it's nothing if you look at stuff that's actually used in the uvolas look at bitcoin what's the fundamental publication of bitcoin it's a white paper it has never been officially published it's on a web page maybe if the web page goes down tomorrow what's going to happen if you want to have a journal where you can send in your white papers your small medical studies don't get published otherwise your technical reports etc your master thesis if you want no peer refu because no way to have a peer refu for white paper only tell you if your white paper is actually complete I mean I was looking at some white papers in the blockchain domain and there were like only written to the half and then it's like okay to be done to be done you're not going to publish that but as long as it's completely going to be published and we want to the idea here is to save that information for future researchers we still have a problem though so we could be traditional publisher we publish on our web page we publish in paper and then our web page goes down and the good thing is we have open access we have copy and copy online but how do people find that copy not easy, it should be much easier so who guarantees that articles are yet to be persistently available and the next thing is who guarantees that stuff is actually authentic where you can trust us but maybe you trust more the original author and if the original author can sign his work put the hash in some blockchain much better and the interesting thing when I looked around is that there's actually no guidance by this published publisher how long this stuff is online I can pay a few thousand euros to Elsevier and Elsevier doesn't promise me availability online for even a year or something why? it's crazy, it's not costing that much and that is and here last time it was with the open publishing island 80% of all scientific data is lost 3 years after publication and the funny thing is the same happens to great literature so 80% of the great literature that's put on the web page of some university or something is lost after just 3 years and but it's not something that should happen so we can use blockchain tell me to tell you what blockchain is we use blockchain for authenticity if you publish with us we put the hash of the article of the data on a blockchain everyone can follow the blockchain so you know what has been published with us everyone can check if it's really the same article and if it's signed by the author everyone can check that the author is actually the correct author and the next level would be to have the refuse also on a blockchain system and to have availability if we thought about using IPFS so the idea is when I think about IPFS I don't know if you probably have heard about IPFS when I think about IPFS is if I put a document out on IPFS it's available to everyone using IPFS if someone else in the world maybe in Africa downloads a copy of that document to his IPFS note we now have 2 copies if it goes down he's going to serve if 1000 people read the article on IPFS we have 1000 copies of IPFS of the whole world so that's really cool that makes data really really safe in the network and this is why we decided to use IPFS to store that stuff and the next thing about interesting about IPFS is the content based reference system so if I prefer a data set that store in IPFS I'm just using the hash of the data set so I can be sure 5 years later if I download the data set with that hash from IPFS I'm getting the same data set that was published 5 years ago that's great and that's more or less what I wanted to tell you reason why open science is important why open science is the way to go in my opinion science and why we actually need distributed systems like IPFS and blockchain to solve the problems that I involved here if anyone wants to publish with us I'm here to play tomorrow we're looking for editors, reviewers authors more than anything today would be great yeah can you give an example of the sorts of subjects and things that you are publishing or are looking to publish the idea is to have a journal for everything so it's a mega journal why should I now I guess when I can do an easy search separate subjects into journals so right now I think we can put everything into one journal actually I don't really think we need journals we could put everything together and just search on it for us it was easier to use existing software the open journal system and there I have to work with journals so we work with this way so open science has been around for quite a while the idea in your opinion what's like the most important thing that keeps everyone from doing open science clear answer the institutional pressure like the incentives I tried to be a professor didn't work out why because I didn't play the game of the imperfect so I wanted to teach students I wanted to gain knowledge and give that knowledge away to other people and that's not how it works if you want to grow in the academic system you have to follow the rules of that system and the rules of that system