 Yeah, I am Amit. I would just be kind of setting the setting the context of the talk and just, you know, coordinating or moderating the session, the discussion section prior to this. We'll go live now, Amit. Oh, we are live. Yep. Okay. So hello everyone. Welcome to another session on privacy matters at Haskeek. So I think I want to probably set a little bit of context of why we're doing, you know, privacy mode, this kind of set of conversations around privacy in under Haskeek. You know, we've been talking in India for a long time around, you know, data privacy and, you know, privacy related initiatives and you know the privacy mode initially started as kind of this conversation around, the digital privacy or the privacy law look like right and from there on it's gone on from that small ambit to thinking about what the digital privacy law would look like to more broader around, you know, data privacy, much much broader context both in terms of personal data and non personal data. And to what we're trying to do now with the privacy mode kind of set of conversations is really help get people in the industry in research community, trying to talk about what are the challenges around the set of, you know, operational challenges, tactical challenges, strategic challenges around how organizations should be thinking about data, how they should be thinking about managing data, how should be thinking about working in a data in across the ecosystem. And this is really important for a lot of, you know, people who are being participant in the Haskeek conferences or community not only as technology product leaders but also as product leaders or business leaders, right. And so we're now in like this privacy mode set of conversations around thinking about helping lay what I would say like an architecture or conversation or let's say framework or vocabulary that everyone can start to talk around how we think about data and data in a probably in a much more decentralized manner than we do right now. And if none of you have joined the scene the previous talks we've had three talks right now under privacy mode, which were really around this topic so we had, you know, Paul, Robert and Philipp from Human Colossus Foundation talk around, let's say the four layers of decentralized architecture and we focused on three talks, one was decentralized semantics, while the one was in decentralized authentication, and the third was around distributed data governance, right. And I think those kind of set kind of the vocabulary and a lot of these conversations that we want to continue and have, you know, different people in the industry as well as business as well as public policy start to think about how to do this. So today, you know, we're going to deep dive into another aspect of this which is, which is going deeper into the semantics question around that. Right. And so we, we already know the two hardest problems in computer sciences are, you know, as they say naming things and cash in validation in some way. Right. And how do we get names for things that are consistent, right, persistent, consistent, persistent. How do we ensure that people can actually refer to it people can identify it. People can say this is what I named it. And this is what makes sense to name it. And if they say this is not no longer the name how do we invalidate it right and in sense those are two hardest problems computer science those are two hardest problem in managing data, right and anybody who's managed data is like, how do I name things how do I figure out this is the thing what it is right as we in data science say 80% of the job is cleaning the data was just basically what the same thing how do we how do we know what is a real object in the world. And as we think about these brain foods of data, you know data processing pipelines, the risk associated with holding data maintaining data cleaning data. When you think about how we can manage this in a better way, right, and there are fundamental ideas around that some of that we got covered in the previous talks around decentralized semantics and decentralized governance. And I think today we want to go deeper into one particular example of this of how you know distributed identity identifiers can be used as persistent identifiers to with probably much more benefit than what we've seen and to do that. We have Dr. Kali Hutema from University of Guelph who's going to be taking us through. Let me let me put it as one of the cases or one of the applications around this around this topic right and I know Paul has talked about this topic in decentralized semantics so maybe I'll get him to come on board and you know introduce Carly maybe set the link from his conversation in case for people who have not watched this and then we'll get passed on to Carly to kind of take us through her work around decentralized data systems especially focused on the agri food side and how maybe watch and learn a little bit of examples around that right. So Paul, do you want to set it up and kind of you know help people get the context to some of the people who may not have watched your nice conversation that we had in July around decentralized semantics. I'm sure thanks Amit. Yeah, just just in a nutshell, I did a talk as part of the data governance and semantics series on decentralized semantics. And what decentralized semantics ultimately does is it enables different tasks specific objects to be controlled by different different actors within an ecosystem, for example. It's really about, you know, ensuring that all of the tasks are separated so that you can kind of integrate them into a semantic stack and and at the resolution side when you're resolving a credential or a form or stuff like that you can kind of do it fairly dynamically. You know, within within a multi stakeholder governance framework underneath that. So I've been working with Carly quite closely at where we're working together the University of Guelph and Human Colossus Foundation so it gives me great pleasure to introduce Carly. Carly, as you mentioned, works at the University of Guelph, developing AgriFood data Canada, which is a distributed data ecosystem for AgriFood research data. And, and the talk that Carly we're giving today is is for the research identifier ecosystem where a decentralized identifier is a persistent identifier with benefits. So just to kind of give you a brief overview of a decentralized identifier that's a new type of identifier that enables verifiable decentralize authentication, if you like, and then, and then if you like, and then persistent identifiers are things like, well, they're basically long standing reference to a digital resource. So, you can think of things like, you know, do is those sorts of all all kindies, those sorts of things that those would be considered persistent identifiers. So, without further ado, I will hand over to Carly and who will give the next talk as part of this fantastic series. Thanks Carly over to you. Great. Thank you. Hi, so I'm Carly Hyde ma and I'm going to be talking today about the research identifier ecosystem. I hope to convince you that he did is a PID with benefits. So this is work that is currently being developed is being incubated at the trust over IP foundation. And it's informing my work in AgriFood data Canada at the University of Guelph. Now, in the research community, researchers need to be able to unambiguously identify object. Now, single objects such as which particular instrument was used for the measurements or this particular data set was a result of these research activities or methodologies or tabularies. These are all things that could benefit by having a identifier. Now we can take that idea even further because with the creation of compound objects. So, so we would have like a project compound object where it would reference the people and the outputs and the funders that were all part of a particular project. We can do the same thing for publication. So a lot of research information is disseminated via publication, which is a collection written by a set of authors. They'll describe the methodology and maybe in code that's used instruments that were used the data sets that were generated. And this can all be expressed as a single object. And finally, versioned objects are another example of things like you could have a publication and version one, version two, version three, etc. So it can all be called the same thing, but you can follow the history along. Now, when we're able to identify these research objects, we can link them together via the metadata. So the figure example here from Project Fran, we know that A and B are related and B and C are related and therefore we can assert the relationship between A and C because of something that we call in research the PID graph. So a PID graph is that that we can view a network of the relationship between objects that are generated in research. So here we can see A, B, and C in that example and I've extended the graph. And by following the graph, the idea is that we can jump from say a person to their paper and their methodology, finding therefore a related paper and related data sets. So traversing the PID graph. And there are many benefits being able to do this. We can generate insight about the research that is being done. We can follow funding to see, you know, after this funding thing, these are the objects that were generated. Finding out what the community values, the thing that the communities reference constantly or to explore new relationships to be able to find new collaborators who might be working on related topics. We can discover new objects for research like a new data set and assemble new sets of related things and ultimately perhaps to identify gaps in knowledge. So to uniquely identify the object to find the description of the object and ultimately trust the results. In research what we need is a globally unique identifier that's globally resolvable to something useful and within a secure ecosystem. And in research we call these things PIDs, Persistent Identifiers. Now the current state of PIDs is that we have an identifier such as ROAR or RAID or DOI. And when you have that identifier you plug it into a resolver which then usually searches some kind of database to find a unique record. And from the record you can then find the metadata and associated links that were originally associated with that identifier. So in this kind of system of current state what you need is you need a centralized database, you have centralized control of that. In the majority of Persistent Identifiers there's a predetermined schema choice and there's really limits about what can be identified. So if we want to get to that state of the PID graph to be able to unambiguously connect from object to object we need to be able to describe many different types of objects. Now I'm proposing here a new improvement for Persistent Identifiers and that is the idea of decentralized identifiers. This is a new concept that's being developed. You can see that many of the Persistent Identifier pieces are here but they're just rearranged. We still have an identifier and that is resolved, we use a resolving service to find the record that's associated with the identifier. But here for example we can have those records on some kind of distributed ledger. And then ultimately we're pulling out the associated metadata and any links that are related to the object that we are referencing. Now there's many benefits to having this kind of system of decentralization. We have a robust decentralized network, there's transparency, trust, traceability and with that traceability and the associated digital signatures we have auditability. And that means that it's a very extensible system and there's lots of opportunity here for innovation. So people can create new things in the ecosystem while maintaining high trust. And this is very key in that it's a governed ecosystem. Certainly in the research identifier world we're talking about we would be looking at building a system that is extremely governed. And that is yet to be established, that would involve many stakeholders and the governance is going to ask how much of the ecosystem is directly governed and how much is open. Who for example is allowed to write different schemas, who is allowed to register identifiers. Perhaps the ecosystem might want to limit where the identifiers can resolve to or the role of endorsements. And all of these choices can be tweaked because one of the key points is the funding model. So often funding is at a national level, but the need for a global system of resolvable identifiers is an international one. So governance is going to have all kinds of choices to be made about who could join, delegation, etc. And this is ultimately going to dictate the functionality of the distributed identifier ecosystem. Now what about trust? How does trust work in this system? So how do we trust the results? In the current state what we do is we trust the centralized authority who controls the records in the database. So you have a number of people who are privileged to be able to log in and are allowed to edit records in the database, and we trust that centralized authority is better used. Now in decentralized systems such as the did system, we have trust that's built on asymmetric cryptography. So asymmetric cryptography relies on keys. Anyone can independently create a private sort of public key pair. And then when you sign an identifier with a private key, you can mathematically confirm that signature using the public key that's available. So conceivably, anyone can create and sign identifiers, but no one can create an identifier with your signature. So we have a new way to trust. So we're moving beyond the idea of passwords and central authorities who do the vetting to private keys in digital wallets with the public keys that are available on the ledger. So the basic parts of the ecosystem for decentralized identifiers that I'm describing here. First thing that we're going to have is what we call the did document. That's the object that's signed by the creator and it represents the object. It's going to be the one that has the links to downstream resources like the associated metadata of the object, the URL of where you can find the database, etc. And the location of this did document in this example, it's on a distributed ledger. Now, the W3C is a definition of decentralized identifiers, of course, there's different ways that you can store this kind of information. And the did itself is just a short little string. I've given an example here of a made up research identifier. And that would be kind of the text that you might include in your publication, for example, you could say that the data set is available at did, res, etc. And then when somebody looks up that did, they would then plug it into a resolving service in order to then I find the compile the did document and then trace it back to find the metadata and any external links. And all of this of course is predicated on private public keys. So it also involves wallets for all the users holding their private keys and also possibly something I haven't mentioned yet verified credentials, which might be credentials that let you do certain things within the ecosystem. So let's test out some of the use cases and illustrate the possibilities in research identifiers. One of the first things we're going to ask about is interoperability with existing systems. So we can use this decentralized identifier to point to an existing identifier. So my object already has a PID in this example is got say a DOI for paper or something. So I can create did that just resolves to the PID and it will be cryptographically signed by me so that anyone can confirm that I was the person person who authored and controls that. So we've see here the first thing that I do is I create my public private key pair. I've got my private key in my wallet and I would publish my public key onto the ledger of the decentralized identifier ecosystem. So that would say like Harley Heidemann I claim this to be me and this is my public key so that when you find something you could check it and confirm that I was indeed the person who authored the object. Now I the next thing that I would do is I would create the did for my paper that's already existing and the did would just be a reference downstream to the existing DOI or URL, etc. And I would sign that did with my private key. So somebody else then would be able to go and look up that the that they can confirm using looking at my public key that I was indeed the author of that paper did. And the important thing here is that I didn't need a central authority in order to secure and trust my decentralized identifier. So coming back to one of the key ideas that I introduced at the beginning of the talk, the idea of creating different types of identifiers currently in the systems that we have right now it's hard to do. So what we ultimately have is that, you know, if we want to create an identifier for a person, then we have to have international collaboration. They'll write about what kind of information belongs with this identifier. Then the in this example it's known in research as an orchid ID or orchid and and and they will run their own database that has all the entries and then we come along and we say no now what we'd like to do is collections projects so the raid identifier gets international collaboration, and they set up a database they build a resolver they secure the funding etc. So you can see that it's as it as it is currently being used as it currently exists it's difficult for new types of identity fires to be spun up so we don't see a whole lot of adoption of the different types of identifiers but if we go back to that figure of a pig graph and being able to follow resources, we can see that it would be really beneficial to be able to give things unique identifiers and describe them with the appropriate metadata. So, with the decentralized identifier ecosystem, it can be very easy to create a new identifier type in the system and and to have the high amount of trust that goes with it. So, in another example of a use case so I am the society Canadian society of microbiologists and my user, my membership has identified a need, we want to create a new microbiome identifier type so that people can give their microbiome research objects like a sample, a decentralized identifier, and they can describe it using this new community schema. So, so in this example then here's a different variation of governance so perhaps a governing body says grants the CSM and organization their credential that grants them the right to publish schemas in the ecosystem so maybe in this kind of governance model we say that schemas are only allowed to be registered by certain parties that have have been granted that way. So, what the CSM does is they are going to, because they have the permission for it they're going to write a schema, and then they're going to create a decentralized identifier that points that schema and they're going to publish that on the, they're going to publish their, their did document and they're going to sign it with their private cryptographic. Now, let's use that new microbiome schema and we're going to mint a new identifier so Alice she has a microbiome freezer sample she's been attending she's a member of say Canadian society for microbiologists or she just appreciates their work, and she wants to give it. She wants to give her freezer sample identifier, and she wants to describe it using the CSM microbiome schema. So what the first thing that Alice needs to do is that she goes out and she finds the CSM microbiome schema perhaps on on the CSM webpage they have published a list of schemas that they support or endorse or or that they are authors of. And that's maybe the way that she enters into this ecosystem she found the the identifier for the schema, she looks it up, and she can confirm that the CSM were the ones that digitally signed the schema did and she trust that she has found the correct schema, because she goes and she looks at them, they're decentralized identifier she looks at the, who signed the schema, and she confirms that it was them and then she's able to go follow the links and find the actual schema. So now what Alice is going to do is she's going to write metadata for descriptive data metadata for her sample that she wants to give an identifier to so she composes that metadata according to the schema that she had found. She's going to reference the schema that she's using in order to write that metadata, and then she is going to create an identifier for the metadata record that she has just written. She was able to sign that identifier with her private key so that anyone can look up and confirm that yes it was indeed Alice, who wrote that who authored that microbiome sample, and she was the one who registered the decentralized identifier. Another use case that we can talk about is the ability to create a compound object using a schema and and have that compound object reference other identifier so for example, we find the schema for publication object and, and it will say that you need to contain different features like authors, datasets, etc. So you can write that metadata for the publication and then give it an identifier so that people can find that publication, and then the publication itself can internally say oh the authors were that referencing the specific author did and the data set identifiers as well. So you can write compound objects and they can contain references to other objects. So with this system, we have interoperability with existing in systems of identifiers so it's very easy to add new realities. It means that we can create a flexible system that enables creativity. You can have researchers controlling different aspects of the ecosystem that they are able to build. And since everything is signed, there's going to be full providence and this should ultimately handle enhanced reproducibility and in my little examples here there's a lot more of the technology that there is than what I have discussed like open wallets, key management, carry for those in the know, revocation lists endorsements licenses and so on. But the, the, the next step after all of the discussion here would be to start making governance decisions about all the different parts that are possible how to put them together in order to make the ecosystem of research identify. Now the technology that I'm talking about here parts of this ecosystem are being built right now. Now I'm not the first person to come up with the idea that decentralized identifiers are great examples of kids in research. I didn't see this but Marcus Savadelo presented Kailiah Young's work at the 2019 Pitipalooza. Pitipalooza is a conference about research identifiers, and I guess they needed to make the topic that is admittedly a little dry, a bit more interesting so this figure is from Marcus's presentation where he compared decentralized identifiers to all kinds of other identifiers that are currently being used. And I added in here that indeed the dids are unique for being the ones that are cryptographically verified. Another example of some of the technology being in use right now is that of Glythe Global Legal Identifier Foundation. So they are using authentic chain data containers based on carry. And in this example Glythe is a root trust for identity. So these are after the 2008 financial crisis Glythe was an organization that was founded in order to give all business organizations identifiers to help be make financial transactions more assured. So they are now setting up ways to do this with a cryptographic verifiable LEIs legal item. And here in Canada we have starts of another decentralized identity ecosystem. So some of the promises are contributing to a Canadian Hyperledger Indie Network called CANDY. The idea is that Canadian government entities can be given identifiers and they will be able to issue and digitally signed verified credentials. And the governance for this is available readable on GitHub and the link is down below. So you can see some of the efforts that are currently being done to with different parts of the tools for the ecosystem of resistance identified. And as I said before W3C, they have, you know, now recommended officially DIDS and VCs. Canada is also looking towards digital trust and identity and is certainly referencing the standard as well. So I hope that I have convinced everyone here that DIDS are indeed PIDs with benefits. Benefits are robust decentralized network, transparency, trust and traceability. Everything is digitally signed. So this means that we have the possibilities for auditability, very flexible, all the components can be remixed, accessible to new use cases, and ultimately an opportunity for more decentralized innovation. I really like this ecosystem and the technologies that are part of it because it means that we can start to become a bit more creative with how things get mixed. People can create new things within the ecosystem, but then they're still able to maintain a high degree of trust. Thank you very much. Great. Excellent. So Kali, that was really, really illuminating to hear you talk about but PIDs and DIDS with benefits. I mostly have a set of people who probably would have questions around kind of the cases and, you know, going deeper into this so that's kind of the conversation that you want to go more on it. So, but let me kickstart with maybe maybe a question. And I think I kind of post this to Paul also earlier in the sense of, you know, the W3C, you know, has been trying to do the decentralized IDs for a long time right federated IDs was before that. And we've tried schema.orgs and, you know, many different ways that were initially tried to make the semantic web so URL itself as kind of the, let's call it not verifiable in your diagram. It was, it was not persistent, it was outside the diagram as a domain name. And I'm trying to think about how much time it has taken us to build that infrastructure. And is there a way that we can build on this or we have to recreate the entire governance for each and every identifier we create. It does sound like now we have new URLs, and I'm calling them URLs but it's like did colon, you know, let me call it Amit caps like my, my, my personal colon something which just sounds like I have a new URL, your universal resource locator, which is maybe cryptographically verifiable. And we nearly everyone has to get to this do this again right like every ecosystem has to decide who's the governance who is to do that and the web already is decentralized and has a lot of this certificate transparency on all of that so I'm trying to figure out, maybe we can speed up that process or combine that we leverage the URIs also as the IDs or is there a way to merge that rather than getting this governance going again around each one of them is just taking a long time to even work right now right. So I don't know this was my thought. I mean, the challenges is that like the thing with the with the persistent identifiers is that the, the current structure of the web doesn't meet though like it is not meeting those, those requirements. So we can definitely leverage some of the the technologies and stuff like that but I, I agree. There is, there is a new paradigm and there's going to be work and investment. Personally, for example, I'm really sick of passwords and and the 50 million passwords that I have for different websites and then and then you go to federated ID, which is, you know, someone else controls all your passwords. And then if if you disagree with someone else then all of a sudden you lose access to everything. You know so these are these are. This is the current system and those are the current risks and I would like personally to see the locus of control come back into into my hands and and what the technologies are trying to build is that you wouldn't have to manage this so well you would be managing a wallet and your agent would be the one that was keeping track of all the decentralized identifiers and, and, and I'm not going to get into into recovery of and sharding and sharding and there's lots of neat things there. But, and then and then as far as for research identifiers specifically like I know that there I have seen like trying to push out new ideas of sample identifiers and and it's just the uptake is so slow that you know because because each time it needs to be recreated independently so um yeah so I don't I, you know I'd like to see in instead of it being done one at a time to be done to build a system in which then you can recreate or build new things having to build a whole new ecosystem each time, but like, like URLs, I mean in research persistence identifiers were built to replace the challenge of URLs because every time a web page, every time a journal article was rearranged or internal structured or URLs would all change then all the references to those papers were lost. So, so the, the, the PIDs were written were created to add some persistence so that you could change the underlying URL. Right. Okay. Hi. Okay, so I'm gonna, I gave me some of your remains, you know if you want to come along and ask colleagues and questions, you know, please, please join. While they come on. Can I would I be able to create a baby. Can I like start my own the ID. Can I just say I am interested in, you know, eclectic books and I don't care about the ISBN and you know do is and I want to class my DID colon eclectic books colon something. And I want to build my own community is decentralized should I be able to go somewhere register and start doing this, or is it going to be large institutions are going to get captured this authority to create schemas and and manage this which is like decentralized but really not decentralized. Yeah, well, what what what I would really like to see is the interoperability so that would be like today with the website. It's decentralized, but centralized in the sense that you know I can pick up my web page and I can change my server location I can go to a different hosting place and I can then update the persistent identifier that is the DNS that would then point to a new location. So, so there. So this this idea is not unprecedented but but if you were when you talk about a did, or do you mean the ability to write your, because you can play in someone else's ecosystem and and using their ecosystem, you know, save research identifier ecosystem went this way and eclectic books was then a schema, so you would have a create a schema for eclectic books and then you would have the permission in order to, depending on how public things are, the permission to write an eclectic book entry, following the eclectic book schema. I mean that depends on how open this ecosystem is and then and then of course, there could be other ecosystems that are more public or more private. And, and now we get into the current construction of universal did resolvers that are being created as well. So it's a right now things are definitely in flux. I quite, there's opportunity here to make the world into, you know, thinking about the long term future of how things how we want things to be because in academia, for example, we have carved off a very key point, a very key piece of infrastructure, publications are managed by commercial companies of journals, and, and all of reputation and knowledge translator sharing happens, leaves academia goes into the into commercial and so we all of course see this and when whenever you try and a journal article is locked and stuff like that so it is a self sustaining piece of infrastructure, which is, you know, one of the goals that people always say but it's also quite a hindrance to academia so so building the ecosystem now means that we can start to think about what what are the cost trade offs we can see in the future. So, like, let me build on that and I assume you have this question which I think kind of leads on to where you were, you were pointing to right like, I want to build a common pool of knowledge or I as an organization to forget like eclectic books. Now we're doing let's say public pedestrian traffic or you know I want to do mapping of Bangalore or you know mapping and I want to create that data sets and some persistent identifier. And I want to get to things right right I want to create some data and get credit for it which is like, you know, I created the schema I created this data, I have, I've signed it I getting the ownership. I'm also want to share it with other people hence the decentralized ledgers. And so I get the right and retain kind of the rights and kids for the work pretty similar to what you know, academic journal example that you gave. But then I also enable it to share it now but the sharing part. I mean, can you talk about use cases on how do you see that manifesting is it going to be a lot more like, again, people who consolidate and manage this graph. of PIDs who would be, you know, the analytics player or the search provider on this graph would say we can look through all this Bangalore data or your journals data and graph and give you the search and then we kind of are again the not the publisher but maybe now the analytics or the search engine on top of these PIDs that manifested. And I think I'm always curious to understand this economic incentive that comes in on this layer, and how that impacts both this kind of decentralized but also how people access this decentralized right so maybe a few more cases that you think really cases that would be good to build up. Was it true or am I Yeah, the question. Yeah, yeah, so let me let me let me start anyway so first of all with the with the identifier ecosystem that I'm talking about. We're going to keep it simple it's going to do one function is going to link and identifier with with whatever you want to stick at the other end so so there is no the data itself is not controlled by the by the controllers of the ecosystem of their identifier ecosystem. So you could for example, you can have you know you can put a data set up and you can say I'm going to give it a did identifier and you can also give it a do I identifier and and in fact within did the did specification you can say also no one as and give other persistent identifiers that that data set is no one as and so so first off there's no ownership associated with the data sets. It's just a pointer system. I think yeah and, but the, the advantage, or the possibilities compared to the existing pointer systems is that you, you can start to add this cryptographic trust. So, and, and also, it's not it's decentralized which means that countries can cooperate and they don't have to trust you know, Oh, all of our identifiers are on the server in this country or you know, in the server in Ukraine and now all of a sudden we have a massive critical infrastructure piece that's being threatened. So, so that that kind of decentralization is an opportunity, and, and, and I'm not getting into a whole bunch of downstream use cases but the the right now the challenge with authentication, or an opportunity in authentication is, is to, to manage these private public keys, and, and, and like for example I use DocuSign I think to sign a house, some deed or something like that and I have, have no idea where those are. Like this DocuSign, I mean I haven't taken the time to dig into it because I was you know in a Russian that was done and stuff like that but where are those keys and can I see them and if I change computers have I lost my signature and do I trust DocuSign to maintain their central registry and can I go in and confirm that it hasn't been edited or changed or something like that. So, so by the, the similar I, so the ecosystem doesn't exist but I would think it would be very important for all of that information to be publicly available, even if not everyone in the public can write to all parts of it or whatever. And, and, and of course then just as, as the web, the web pages are publicly available. That means it's a data source for others to write you know some kind of data crawler in order to you know construct these pig graphs to construct artificial like to look and say oh, here are the, this, this schema xyz and here are the 500 data sets that are using schema xyz and we've looked up all that information on, on this registry of where the dids are registered. And then your construct a virtual data set that references the 500 data sets that are all using the same schema doesn't mean that you have access to all of them you just have their locations and then, and then, you know, this is part of what we're considering at AgriFood Data Canada the University of Guelph is then, you know how, how can we smooth with machine actual governance the access to data sets, etc. I think let me, let me take the Steve's question here because he's, he's posted on the chat, you know, individuals can create their own DID without permission for anyone so that's great. But if that goes is as far as it goes that it's not very interesting, you know, building a valuable community around is taking my example of eclectic books, for example is the hard part, right. And I'm also curious on this right like I'm trying to think of nobody wanted to create schemas or semantics for the web pages right and, and the only reason everyone started to create is because the crawlers, the and all of them started to say, you know, all the Facebooks in the Twitter started to say have this open graph have this schema have this the IDs and then we will do the crawling and right now it's not persistent but they're still, let's say, extracting the data and creating some search a graph, like you're saying in the IDs and creating it right so building that valuable community around that is hard like forcing people to start using that is the hard part. You know, that's what I guess he's, he's kind of referring to like getting people enough people to use it and the economic incentive advertising or, you know, making my webpage accessible was enough to push a lot of people to start putting in a little bit of semantics on the web page, not too much, but enough for the crawler to work. And, and I guess the question is how do you create these communities around these schemas or the IDs that make them sufficient enough that everybody starts using it and starts to make it work. And I can also see Paul has raised his hands up for you. Do you want to answer that question or do you want to take a stab at it. Yes, sure. Yeah, I think the important thing is to differentiate between identifiers that are events and identifiers that are objects. And, and what I mean by an event is you know when you enter information to a system that needs to be verifiable that has come from an authentic source. And that process there is identified through an event identifier. So you can think of kind of decentralized or DIDs from the decentralized identity community as event identifiers. That's exactly what they do. They have to prove some kind of provenance of the data going into the system. Whereas object identifiers are in a decent in a distributed data ecosystem, the underpinning of those identifiers needs to be deterministic, meaning that it's basically a hash of itself right so that the identifier is a hash of whatever that object is. And, and, and the control that keeping those two things separate is really important so the control comes from the DID space, whereas the, the everything in the semantic space is a unit of language right and so that's that's just making sure that there's something that an object is deterministic. So if you kind of think of it that way the control of objects can be can be determined by linking a verifiable credential to those objects and the verifiable credential is where the control comes from. Because in the semantic space, there should be no control. It's it's all about deterministic objects. It helps it all ammit but it just kind of, I just wanted kind of people to think about that a little bit. So when they talk about semantics and issuance and stuff, you don't necessarily need to be burning that that issuance part into the schema, you can be basically linking those objects to a verifiable credential that proves that you, you're a controller of that object. I think I think that definitely helps so I mean we're saying we're not embedding the schema part into the object itself. I mean the link to the hash is the object in the schema and everything is there. So DID because of this namespace thing that we're trying to do is inherently creating instead of dot com dot r dot r now we have, you know DID colon research, right, so that schema event is again communities or sub communities or ontology that people are on topics and I'm saying so let's say I'm interested in eclectic books and I create that eclectic books community or that schema and then any object in that is probably of some eclectic book. But I whether you can access it or not access is separate. But at least you can get a map of all of that right but now I guess that's what Steve's trying to question is the hard part about this is getting enough people to start using eclectic group like DID colon eclectic books colon something. Until that happens, the efficacy of all of that is is is not really that great. Now whether it can be generalized across a lot of these research things that will be helpful, obviously if we all start using DID then doesn't matter if I search for DID books was eclectic books and all I can start to do that. But I am just a jump in there. You know, these are really kind of governance issues right so you know when you have a multi stakeholder governance within that space you know that that's the, the voting members if you like of that ecosystem they need to be, you know, consensually agreeing to the to the stuff that they're using for their ecosystem, because and they have to do that so that you can harmonize the data, because it's really difficult to search for data unless it's harmonized. I want to share a couple of examples of like governance models that have worked on both public, public, you know, gearing goods as well as private. Yeah, just before we move on I just wanted to jump in about Steve's talk again about the community and that the research community is uniquely positioned because we already are an international group that is already using precision identifiers so you know in your paper when you write DOI then you would write did you know, you might use DOIs for papers because that's the community standard but then you have a sample or something else and you would say or you know, I organized my data, according to schema did such and such. And, and that means that somebody else who's research, who is doing similar research says oh, you know, somebody else has already done the work of writing the schema that has, you know the fields that I'm interested in so then they write their paper and they say I wrote it according to schema did such and such. And so so within the research community. Indeed this is already practiced and the ways that we disseminate is through publications or talks or societies and stuff like that so so there already is indeed this persistent identifier universal identifier needs to be adopted in research it's going to be pasted on to an existing community that already does stuff like that. So the difference would be now those dids for instead of DOI DOIs would be probably verifiable. So you can say as an organization or as an author. So this is my DOI I confirm that, rather than getting a central authority to issue you a DOI which is what maybe a publisher does or a book amount of, I don't know about enough about the OS but is being as issued by like different different regulations in different countries. So, and you have to, you have to, you know those organizations then absorb the cost and they charge you know it's like a dollar or something like that for every DOI registrant. That's the funding model and but the thing is is that they, they, while the DOI system could be flexible for other digital objects I don't see being used that way and usually there's a few large schemas that are being adopted that are only used for publications or mainly just what I see is publications. And, and, and with the way that we could build the did infrastructure we could make it so that it's much easier for individuals or groups to write schemas so that they can start cataloging the very specific things that they need. Can you, you know, share the example from like your work at Agri Agri food if that's kind of or the Ontario example like build a little like this I think some use questions really valid to, or, you know, I think a lot of us. Maybe we have blockers because we know what what we do now, and we don't see enough examples at least definitely in India around how this could be done in a decentralized way I mean we have centralized databases for everything, including identity. And, you know, we are, we understand that but how could a decentralized thing whether you know the example in Agri food or the Ontario example that you were or the cross province examples on public. I don't know what around what that topic is could you shed a little light on that could help people understand some of the use cases and connect to what they're doing and works. Yeah, yeah, so, um, well, I mean, the, I mean there's, there's a lot in the technologies, but if I'm going to talk just about the persistent identifiers these global identifiers which is directly related to the talk that. So at Agri Food Data Canada at Guelph we're not looking at identifiers yet that's, you know, this this identifier work is my work and it's informing some of the work at Guelph and Guelph is looking at how well so we were we were trying to come up yesterday with how to describe it and the idea that came up with it imagine if the web was centralized. So it'd be somebody would manage giant silo and say, Oh, if you want to write a web page, everybody logs into our web server and everybody puts all their web pages on the same one. And, and, and, and, and we have all the rules for it and, and, and, and so on so this this and there's a single place that serves up all the web pages of web. And that's the that's a centralized model and you know there's efficiencies but it's also a giant honeypot or risk for attack. I remember one of the quotes so in European in the European data, data space for research data they talked about if they wanted to build a silo for all the research data in Europe, they would have trouble like cooling it. And, and, and powering that kind of thing in a single location so so we can see the advantages of decentralization where we have many silos in in the decentralized example it would be the database of all these pointers these decentralized identifiers, distributed through a series of nodes, just like you know in a in a ledger system but for those, you know not with the huge amount of proof of work not all ledgers are Bitcoin and not all ledgers require huge amounts of electricity in order to solve puzzles that's the game of mining, which is you know this that not not all ledgers are are Bitcoin based. You know, something like this can operate much more efficiently because you're not using proof of work you have cooperation and governance about the nodes that can participate on a global scale and I mean, real world example I mean so the system that I'm describing parts can be repurposed to a whole bunch of other stuff like a whole lot of other stuff, but specifically my example here of persistent identifiers, where you would want to, you would have some kind of global cooperation or want to you know start to say that you can unequivocally identify something uniquely so I did one of our earlier discussions like that. Like, you know, you can have multiple organizations and they all might want to call the same lake or the same well or the same field they'll have different names for it and stuff like that so this becomes really difficult to to communicate and describe and search and databases, mergers, etc. So if you have a group that wants to share amongst yourselves and a single identifier and and you want to distribute that information, and so that each group can independently, you know, upload and control the records that they that they that they are working in. And then, then this is the kind of system that that could be adopted, but it's it's not if you're if you're just a one off. If you're, you know, if I'm if I'm, you know, running a shop and I have my warehouse and I have all my objects in my warehouse I'm not going to make a big distribution system in order to give them persistent identifiers I'm it's where it's where you have control between different parties and and you know they might have different incentives and stuff like that but they're they've agreed on this one on this one part and and and they, you know, they globally don't have to argue about you know where it exactly is and who has the direct control and so there's this flexibility of design in it. So that's a shared document. No, I think that's that's helpful because now I think at least I'm getting some better ideas around where we could apply and I think Steve's also on the chat shared a document which is a link of options by different public sectors and private sectors around, you know, a lot of the ecosystem around all of these verifiable credentials at least and some of them are based on these ideas I think that's useful for everyone to look at I think we will post that on the chat or other resources also later on. And I think this cross industry thing is really doing I mean I guess I mean given I have a little bit of background in retail or consumer products are, you know, like the idea of barcodes or scanning for food, you know, or scanning passports and having same passport scanners across the world. I mean those are identifiers globally agreed by different communities or different ecosystems for making something efficient people passing through channels or containers passing through our food passing through a checkout counter. And those identifiers we all recognize or they are still centralized and government and you know within that community. And I think this idea of verifiable pointer as you kind of, you know verifiable pointer to the schema that really helps kind of make some of these possibilities make better. Before I ask, did that kind of pick up your question or do you want to come on the mic and maybe ask a further question if that didn't clarify. Thanks, it did help. Of course, as I'm imagining it, we were in fact discussing how these data sets could be decentralized. But I think then there are earlier battles of at least like a meta schema emerging because like I was telling Zainab, the battle we are fighting right now is the not invented here syndrome across researchers and research orgs. Okay. Do you want to give a little bit of more background because I think Carly and maybe I also don't have enough of the like just share a little bit of background and like how we could think about a DID in that context or would it even work in ignoring. Yeah, so just to give you a quick background, this is data commons being imagined across people doing work with land use and land cover data sets across India. Conservationists, people working in water, people working on, you know, the hydrogeology of a region and so on so forth. There are very large pockets of data for specific geography, sometimes deep, sometimes pass. And the idea was to have like an India wide view emerge from this. There's pockets of, there's layers of tools that can then exist on it and may be accessible to anybody working on the field. So there's a speaking to over half a dozen orgs, trying to do this. Of course the data exists in a variety of different forms and formats, right, sometimes very dense PDFs and nothing else. So it starts from there, but I can see how this would, because one of the questions we did run into is, you know, especially when you're talking to research orgs, there is the question of who owns the data, right? Right. So we were discussing. So who collected the land use data or the hydrology data or the mapping data and like how do I get credit for that work or the collection. It's not part of it, but just like an identification of where it is, because it's also a question of the source of the funding. The government has its own set of regulations and restrictions around it, where it can be used and where it may not be used. So you need to be able to trace it back. So it's essentially a question of being able to identify where it came from and being able to manage it using a set of rules. There's also, of course, other questions around the data qualification and other stuff, but that's slightly outside the purview here. And do you see something like, you know, like I'm sure in land mapping and all that, there are already DIDs or some kind like, you know, census blocks is the US thing, but in India we have probably area demarcations and blocks. And those are like unique identifiers or something that can be used as persistent identifiers across that and you want to then have different. I think something like that will be needed, especially if it's distributed, I don't think getting away from that. Of course, before we have an agreement on what, like if you go with the government definition of blocks and stuff like that, you have administrative boundaries. I don't even know if we can do it through one set of identifiers, or we actually need a variety of sets because, you know, just getting different research orgs to agree on how they look at the map is really quite challenging. Itself is a challenge, yeah. I think that, I think, Karli, I don't know maybe you have pointers on how you got, I mean, even in research, right? Actually, I don't think people have enough background on how DOI also emerged or, you know, one of the ways to think of these decentralized identifiers and getting consensus around the schemas or how, what will be acceptable to be saved in this DIDs. Is there a process around that that you can help people think about or, you know, lay some guidelines or pointers to that? So schemas are excellent and not well used. I think that's, in research data sets and certainly when I was doing research myself, you know, it's one-offs kind of thing. You're not really even aware of standardization or the need to standardize because, you know, you're just, you've got small measurements or something like that. As we're talking about interdisciplinary research, trying to combine, you know, like, now it's not enough about, you know, just crop outputs. We want to know about crop outputs and ecosystem services at the same time, you know, to more globally optimize things. It's becoming more important in order for data to become more interoperable. Now with these, in fact, I think it's mainly, I think the schemas, there are the few schemas that we already use with persistent identifiers. Those are a very top-down prescribed. So, you know, they'll have an open committee, presumably, and you can, you know, however their governance structure is for membership, either you're contributing enough money or you are a volunteer or something like that. And then, and those are writing the few schemas that are currently in use for databases and like DOIs, or kids and whatnot. But the ability to add a new schema is very limited right now because, like as I said, you have to spin up a whole new system. And that's, I'm kind of, within the research field, my personal inclination, I can see the advantages of having top-down larger schemas so that we all work together and become very interoperable. I see practical limitations to that. And I really see working at it from the bottom up, you know, so at Agri-Free Data Canada, we're looking at this from the bottom up. Of course, we support, you know, top-down, you know, trying to set up global standards. But from bottom up, what that kind of looks like is that right now my schema, when I do a data set, my schema is, and I say now modern, more modern times, I would upload the data into a repository and the schema would go be paired with it. Now, when the schema and the repository and the schema and the data set are tied together in a single repository, that it's like it only belongs to one thing. And if what we can do is that, you know, if you're uploading your data, put your schema alone naked in a public spot so that others can, if they want to use your data or extend your data or like what you did, they can find that naked schema and apply it to their own data sets. So this bottom up approach is about working with what you're already doing. And with Paul Knowles and Human Colossus and what we're doing at Agri-Free Data Canada is that the annotations of the schema can be greatly improved for interoperability, and you can write mapping, crosswalking between schemas. So if I have a really well-published schema and group over here has another really well-published schema, and now we want to collaborate on a bigger project, at least with it being public and documented, we can write the crosswalks in order to be interoperable. I mean, in a perfect world, there would be the ideal schema that everybody in the world has already agreed to. And, you know, researchers are... Everyone is very... has their own view on how they want to map the data and how they want to... But I think this is really a great idea. I think because a lot of us think top-down, how do I standardize and ensure everything is collected together in the same format? But I think what you suggested is that the schema is emergent, you know, that different people can connect schemas in different ways and they could all be part of the same thing with different schemas. And over time, we can even have transformers from one schema to another, we can have mappers to do that, as long as it's well-documented, I know what is what. We can then, over time, emerge into a better schema gradually, right? Like, semantic versioning to some extent is kind of that idea of saying, nothing is perfect, we just have another version which is maybe an improvement on that and kind of build on that. And also with these top-level schemas, you know, they might not work for everything, but maybe half of your schema can be mapped to something global, you know? And the inflexibility, the reason that a researcher always moves on to the next thing is because researchers at the age of knowledge. And what's existing is not complete enough to answer the questions, right? So they're going to be writing new schemas because they're going to be like, hey, nobody has ever looked at this before. This part, right? You know, so we've never incorporated this measurement or I have a new instrument and now it does these five things. So I think this kind of brings really this good point because I think in decentralized thinking, you know, in centralized thinking, we think top-down to a large extent, right? We start a committee and build everything. In decentralized as in the emergent schema, I really like this word emergent schema as that emerges over time as more people work on that is really valuable and really valuable as a different way of thinking, which a lot of us don't really put on that hat without thinking decentralized first. Paul wants to say something and I'm sure I am sure he has lots to say on this. Yes, Paul. Yeah, something that also Carly and I have kind of briefly discussed is all of these kind of amazing ontologies that people have been working on for the past 15 years in certain ecosystems and how you can use tagging objects to tag ontology terms to data capture structures that have been consensually agreed within a distributed data ecosystem. And one of the interesting things is like, is by separating the semantics, you can actually give different actors different control of different objects. So for instance, like, if you think about, you know, researchers putting schemas into a distributed data ecosystem, we don't care how they capture their data, right? So they capture however they want, but there are transformation overlays, which are separate objects, which can obviously cryptographically link to these structures. But when you talk about something like ontology tagging, it's interesting because usually the context would come from the source of the data. But in the case of ontology tagging, the only people that will be able to see all of the schemas within the ecosystem will be, you know, some kind of subject matter experts or something within the data ecosystem. So within that, that that governance space, you could have subject matter experts ontologists kind of, you know, doing some of the more contextual mappings on ontologies on an ongoing basis as the ontology is evolved, but also as the as the ecosystem of research for purpose as that evolves so I just wanted to kind of throw that out there something. No, no, I mean, I think in that's a really good point and I think, you know, as Samir has this point on how do you write services and API is on top of these kind of things and, you know, one of the ideas in distributed software is how schemas evolve and how schemas evolution has to be managed and how you can have translation logic from one schema to another. And one of the ideas that I shared, you know, with this idea on lenses that helped you manage distributed data schema evolution. And in our case maybe multiple schemas at the same time and seeing what it is. I think these are interesting topics people are thinking about both from like thinking about how to manage schema evolution but also from a programmatic perspective on a workflow perspective how lenses or mappers can use to go from version one to version two or multiple different versions of different levels of granularity and to do that. And how far can you go and you know where where you need to then stop around schema like you have to some point say this is now the new schema and everyone agree so you, you probably start with distributed stuff then maybe the ecosystem comes down to maybe some common ideas that start to emerge and then you kind of merge on that and then you build another evolution there on that. I think this is I think for a lot of us, I don't know a lot of us but at least for me, you know, working large organizations or backgrounds, less so in public policy, we're more used to thinking in a very centralized way right our databases are persistent identifiers are primary keys. And I think for a lot of us, you know it's how to do this decentralized effectively both as identifiers and as well as you know the data behind it and how to manage it is something that I think a bigger challenge and I'm generally talking about you know, you know technology people that we in Husky kind of see people coming in conferences they're all like businesses focused on a lot of that public privacy so I think it would really be great. Kali and Paul like you know, if he maybe in one of the futures conversations bring bring a little bit of, you know, pride, people that have done it in a non public policy area. Does that make sense like, you know, non government linked area because I think it's easy for people to see it in a in a common good. You know, Commons area as Samir rightly pointed Commons, you know, the tragedy of the Commons and we can all see the challenges and tragedy of the Commons. But how can I make something that I'm doing in my own organization and still think in a decentralized way that will help other people to also connect from it is a lens that we all struggle with. And I think more that both of you can share examples or point people to how to do that to like, just change their lenses around that would be really helpful. Does that make sense. Yeah. Paul, if you have a good one I mean I always I'm thinking coming from academia of course I'm always thinking through the lens of public good and stuff. One of the things one example I can think of now is that carbon capture and carbon capture markets and stuff like that because the, the ways the multitude of ways that one would want to, you know, describe how much how much CO2 say an activity has and there's so many different activities. There are so many different ways to describe the carbon capture from those different activities. And in a private market where you want to be exchanging carbon credits and stuff you know you would want to know the methodologies used to calculate the carbon that goes into the carbon credits right these aren't because these aren't measured they're calculated from from algorithms with a certain set of data inputs right. So I could see like the private sector would benefit by being able to publicly identify, you know, and that the methodology so methodology would be given an identifier we can see who digitally signed it so we can see, perhaps there are you know you know in the market you could say, oh, you know, we want to buy carbon credits but the only ones we count our A, X, Y and P, and because those methods those methodologies have been well validated for our, you know, our country, our business desires, etc. Trust, like I think you're right you pointed out I think trust we haven't talked enough about it but you know that this factor of trust that comes from this verifiable identifier is something that is lacking right now in any kind of identifiers we have right and and I think bringing that in the conversation could also provide the governance incentive and the economic incentive for a lot of people to think about adopting them. You know, and I think when we, when we talk more about the tech of it. I think the tech is the easy part. I know what tech is not the easy part I know takes money but but the tech is the easy part. It's the governance and the economic incentive which are the harder parts for a lot of the adoption style and and I think probably need to think about in our education, like how we can do that, more around these trusts stuff that basically translates into easier governance easier buying for organizations to do it or, you know, I take the example of pass keys right like, I mean who would have thought that cryptographic opinions would start to become common. But now that you know the big players have started to adopt, you know, public private keys as one of the methods to authenticate we can see that there is an economic incentive everyone hates password. Everyone believes no trusts, public key credentials is better and adoption will happen. Well, maybe not now but another couple of years. Hopefully, we will get away from passwords or move away from it as the primary method. I was just going to jump in there and actually say that you know the model that we showed in that I showed in the decentralized semantics regarding the master the master mouse model. Yeah, so that's a fractal model so it's quite if I was to set up a new company tomorrow, I would just set it up to say in exactly the same structure as that. So basically you always have new data coming into the system or into the into the organization, and you always have business insights people that are looking for data to to improve their business. And then in between that you kind of have the the x what we call access management to the to the objects or whatever. So that that model doesn't really change. I think. And obviously as these distributed data ecosystems become become the first few that go live you know organizations that are kind of built upon that structure already can easily start integrating into into the bigger picture. Yeah, but Paul, we are simple people, you know we have struggled to see layers and fractals as easy as like you know the first level. I fully get what you're saying. I'm just trying to say that, you know, it's, it's harder to see that I understand the layers the fractals the fact that everything can be then we can go another lower and start to see that same thing in action. But there are two things in in in companies are really hard right I mean, you know, or let's just say one thing, you know, we can have a great distributed strategy, but our culture and what we how we think about it takes a longer time and very few people are starting from scratch right so as as my consulting people would say you know culture each strategy for breakfast. And you know, how do we get people to start changing that culture thinking that decentralized lens. How do we get trust governance and the economic incentives to do it sadly so you know it's going to drive a lot of this conversation the tech they will figure out. I'm sure they will buy into any tech that you know any systems they will adapt anything as long as there's enough incentives and enough governance for them to do it. It's really interesting because you know part of our kind of deep diving into all of these kind of conceptual pieces, kind of showed us that some things that people, common terms that people are using are kind of a little bit outdated already so you know when you talk about I am identity and access management there, you know, identity and access are two totally different things right so identity is really that's an IT job right that's about authentication making sure that it's come from the you know that the access management is totally different that's more of a business decision so that's you know it needs business leaders to be authorizing people to do certain tasks but it's very much a more of a governance thing than obviously identity. But it's only by kind of going into this and separating things that you realize that some of these old terms in a distributed data ecosystem they're very difficult to shoehorn in you kind of have to separate those pieces. And I think that's one of the challenges not everyone thinks in the distribution like I mean I don't know I shouldn't say everyone I cannot think naturally in a decentralized way other than the web examples that I keep bringing because that's the only one that I can think which is set up in a very decentralized way. Every organization ends up thinking much more in a very centralized way and you know I know the vocabulary is a challenge, the vocabulary is very grounded in the centralized way of thinking. And how do we shift that mindset in our communication in our talks. And I think what we really help and I'm just talking from our audience perspective is really to see. You know more examples of you know people blazing the path on this in a way that is being done. Maybe not just for a public policy perspective but also from a private policy perspective I don't know if I'm kind of, you know those examples really bring it to light that this is possible or open the lenses to, you know that we. There is another word. How do we get into it is, is the next question but let me first see the other word and how do we get people to open that blinders would be really useful. Um, yeah. I'm just reading a smears comment here in zoom about distributed data sets for example. So, um, yeah, well, one thing with from a distributed system would be the idea of authentic data in research for example at the start of the COVID pandemic. There were some studies that came out that promoted drugs and which had amazing results and then they were kind of, you know, the truth travels much slower. You know, and then the disc this discreditation of those research results which were fraudulent I mean they were, you know, in one of the examples I think it was that you know every four rows were copied with changes here and there so once you actually got your hands on the raw data, you saw you saw immediately that kind of stuff or things like you know when they get their statistics group of 11 people exactly 50% had this thing, and it can't be 50% when you have 11. The right has to be some, you know, so these were the kinds of things that were indicative about inauthentic data but they, you know, with with digital signatures and and and perhaps you know, even in the in the far future when it comes off an instrument the instrument usually signs the results so that they cannot be, you know, so that we can have provenance tracking and we can see where changes were and, you know, and when that happened I mean the the field of Alzheimer's research spent decade, going chasing after oh I can't remember but it was it was also it was a fraudulent paper and there were billions of dollars and a decade of research that was spent chasing after this you know original fraudulent paper. You know, authentic data is something that in science we we we trust, but you know we get caught and and and you know eventually things come out and you know but it might take a while and and that's only of course in places that are under active and if you're publishing the one off thing for this one off observation and nobody else really cares, you know, you'll never it'll never be detected, unless you know somebody's going to pay for the reproducibility study. So, I think who audits the auditors is kind of the traditional question around that and you know provides that in the kind of if the topic is important enough other people are chasing it, and you know they'll eventually discover the truth. Yeah. And I think it's harder to do that in in communities where that's not the norm, right, like, you know, I mean journalism tries to do that in the public policy like they're the fourth pillar of the democracy in somewhere to try to observe and call out all of that. But how do we as how can we all check the authenticity verify and do that and I'm hopeful. I mean I'm hopeful like now that I'm getting a sense of all the stuff that Paul and you, Philippe and everyone's been talking about that it should become easier to do this across industries and across areas where we can think about data we can think about the lineage of the data we can understand the provenance of the data we can trust it, or are we if we care enough we can find enough resources to understand it and say whether it's correct or not correct and even consolidate but somebody's asking, I get different data is about air quality right now for example from different sources how do I merge it together. You know how to emerge all of this together in a trustworthy way with different schemas and all of that should become easier in this new world. I can't wait for this world to come I hope it comes sooner than then then then we are going right now. I'm very fortunate and I think it's been really great. You know colleague thank you so much for, you know, spending the time, and you know from Ontario's thank you so much for like getting up in the trilogy for you coming on to this recording the talk. Thank you also to Paul for, you know, helping anchor this whole series and kind of helping us all build this decentralized vocabulary which we sorely need. And I can't thank both of you enough I look forward to seeing more of the work and more of these conversations and hopefully, we'll have many more of these. We're continuing it definitely on privacy mode here at has geek and I think for everyone else. I, we're nearly at the end of our time so I'm going to kind of close it so if you want to follow you can definitely go to has geek.com slash privacy underscore mode or privacy mode sorry just privacy mode, and you can see this conversation the previous talks a lot of the other talks and other work around the privacy more topic. There's also a telegram group that you can join you can find us from there on Twitter and continue this conversation. I still have questions for you at you know what's the best decentralized platform that they can reach you on our centralized you know email or you know, Twitter LinkedIn whatever works for you. Twitter and Twitter and and Gmail so I'm very much centralized person. What's your Twitter handle so that people can. Is there. Okay, I guess we'll put that. We can look it up. That sounds great so you know where to. Okay. Yeah, so your name at Gmail is is pretty much the Gmail and Twitter, we can find. Thank you so much thank you to thank you to you and thank you Paul, and I will also want to thank you know Samir and Steve who been, you know, asking all these questions around here, helping me stay online. Thank you for your questions so thank you Samir thank you Steve, and Carly is that on Twitter at micro bio Carly. So if you want to, you know, go follow her and ask, ask more questions on the IDs and the IDs to her. And we'll hope you have a good, good rest of the day and a good evening everyone in India and a good rest of the day to both of you where we are. Thank you so much. Thank you so much. Thanks.