l blockchain and this is new ways to look at data yeah it's like there are projects that deal with like today there's like this one thing and James said it like once in a good way like today we we give data we trust somebody with the data to do everything with it and just give them some data so we give some data very carefully in most of the case in research world right to somebody to do everything with it right so in the future we might end up in a point where we give all data to an entity they can only do something with it and very constrained things so think of sending all blood pressure data of all patients of Berlin it's my favorite example to a smart contract and that just and it's an internal review board IRB board can carefully review the smart contract and can see line by line that this smart contract is only able to release average blood pressure with a four weeks delay of all Berliners for example that would be a cool new way right I know I know that it's like at the moment it's not possible because the smart contract will leak the data to all every nodes that evaluates the smart contract but they are like publication and then we get into trusted hardware and everything but projects that work on this are calling their projects blockchain if fight data whatever because they have like how do we constrain the access to the data we don't want to have like one entity that is trusted with the constrainment we have several entities right and they call the system blockchain too to like so in this term like the blockchain of distributed trust becomes like the social, philosophical political representation of our responsibility to constrain the access to the data if we like come up with a thing that let's get all patient data from all patients and like send it somewhere we don't want to have just Max Planck server to trust that the data is constrained we want to have all research institutes maybe taking responsibility for that yeah so and this is like it has to do with crypto economies, strong cryptography new data handling ways distributed trust and this should be blockchain as well because we can like piggyback on the hype to introduce in these new decentralized data ways this actually is the most I think we will like in this next session we will talk about this yeah and have talks on that any comments about it or is it okay to call this still blockchain or is it too far out what would you say Ali Ali Ali you command on this yeah you are the computer you know trusted hardware you know that these are still dreams right how did you call what kind of blockchain and no no no not this is it has like this distributed trust strong cryptography a provable ability or auditability yeah all these things it has no blockchain I mean all the blockchain project in the future might not have a blockchain at the end as a data structure right so they can be something right but it's cool to call this blockchain as well if I'm careful like enough okay because it is distributed stuff strong cryptography and you command on the feasibility or later you have to go but I would love to see you like on the next session but okay yeah so one thing is how do you get the data into the blockchain projects they're working on this town crier for instance I think it's a group that's working on this but how do you actually make sure that the data you get inside into the smart contract make sure that it's actually the data you wanted to be in the smart contract yeah that's right but only the smart contract can decrypt it maybe you can just expose it to the outside and only how do you make sure the authenticity of the data that comes from outside of the block exactly that we have identity problem again right I could just create 10,000 of patients and just send it somewhere right so we have to constrain that as well and this is a big problem I agree here maybe a useful way to think about all this is to think about use cases where actually you want to solve like existing problems and you explore the problem space and then you think how could I use a blockchain or whatever technology that is there I think that's the right way to approach it in general yes and to expand a little bit on that maybe there are already interesting use cases out there that you can apply in research and science so for instance we had a super interesting hint to that cache and zero knowledge snarks and imagine that yes you can prove to your text office if necessary that you received a certain amount of money in a certain times man and at the same time to the rest of the world this is completely opaque and nobody understands this and this is exciting and think about this level of autonomy that you have above your own transactions and you can easily as an analogy you can find use cases for that or I see use cases for that and higher education and research as well yes it gives you much much more autonomy against like yeah enough said okay yeah so I just want to like do two things there's lunch outside and we continue and everybody who wants to go to lunch just goes to lunch the other people just stay okay is that okay and we open up the panel at the same time yeah okay so or should we just continue if you're hungry just eat okay just coming back to the data point a little bit like basically how do we see data in blockchain right so the great question is that okay we have all this cryptographic construction so we have homographic computation which means that you can do computation like entirely sorry yeah yeah yeah okay excellent yeah cool yeah it's okay yeah okay yeah yeah this is a very interesting topic yeah so basically like we have data on your head data and if we derive this from first principle that is like we want to use blockchain why? Blockchain is for decentralized trust to create a trust amount on trusted people so why do what kind of data you really want this kind of trusted services is your own data your own generated data your genomic data your browsing history your all that stuff so this is like for data on blockchain or data use case on blockchain is mostly about self sovereignty of the data right so you have genomic data you want to contribute to the scientific research but you don't want to like everyone know that maybe like I will go Alzheimer's like in 50 years so how do we do that the blockchain is a layer to break down the financial barriers to make the incentive work but there are a lot of things that need to be built on top to make this actually work and several key pieces including privacy computing that is like you can do computation on encrypted data and extract some information out of this and you know homographic encryption that is like basically zero knowledge proof that is you can prove something is valid and fit some property saying that okay my blood pressure is about 150 but like at the same time not revealing exactly what's your blood pressure for example this is kind of a thing that zero knowledge proof is and these things that would need to be built on top of this incentivized layer because at the end of the day you're selling your data you're selling yourself so this kind of incentive need to be realized on blockchain in a trust free way so yeah that's my I forgot this like the multi-party computation to like incentivize it that you have in a decentralized way yes that's right this was even the more obvious argument to call it also blockchain this new data handling paradigms so since nobody is going I have a question I'm over here it's totally okay that you just stand up okay I know what I mean like for lunch sorry I really like sitting I'm a little bit confused about this conference because I'm hearing I love that we're talking about blockchain and everything like that but it was my impression that was going to be how is blockchain going to help us in science with all the problems that we really really have and from what I'm hearing is that there's all this great technology but I'm not hearing a lot of how are you going to solve professors not getting tenure because there's so many people still not they're not leaving how are they going to solve the paywall problems how are we going to help people in countries in like Brazil they're not trusted their research is not trusted just because they're not at max Planck for example right so I'm just saying right you as a you have to move as a scientist to be these are the actual problems in science that we really want to solve so how is blockchain going to help us yeah good question we have like we create new incentive structures we create new different incentive structures we submit things blindly but immutably and you don't know whether it's from max Planck's idea or from like some remote country in wherever and some people don't accept this and you don't know whether it's valid it's from a arena it's from a well-known institute or not and you can reveal it later if you want and but people might still invest in it they might they might think it's maybe from Harvard but it's like really not from Harvard you know so they don't know so we have this pseudonymity that I could like think of right or we can have new day value flows we have new systems that can of course be game but the current system is game big times right but we just have like changing incentivization structures that we can easily build on top of blockchain systems because today we only have like one two three systems we have a monolithic incentivization structure we have like all these committees that like come up with review in processes because they have the obligation to the taxpayer to distribute the research money in a very well planned way right so it is this big effort of like grants and grant review and you plan your research for the next three years right like what we address today right but we have a blockchain system you can like rely on this obligation to have a trustworthy way of distributing the research money and in the same time have very innovative new ways so this would be one answer to this one vision now we are talking visions right it is like the phoenix from the ashes like blockchain was completely destroyed this morning now we rebuild it for the next one and a half days okay so just we are chiming on that a little bit also right so if we are talking about real problems maybe like the tenured problem that I also couldn't solve that is why I quit academia and started company so but another thing that you just reminded me is that it may make the flow of public contribution to research funding much more easier so let me just give an example here so in Berkeley there is a project called bonnick and bonnick is about finding aliens so it basically analyzes the telescope data and try to see if there is like a planet that is suitable for human living and maybe aliens like little green guys are living there so that project is struggling right so they cannot get enough funding because you know who cares the finding aliens right so but if you think and there are a lot of projects like that so basically you can install a software on your laptop and fold proteins for medical researchers but no one is doing that these days now but what blockchain can enable is this kind of frictionless payment friction is micro contribution to researchers right so you could now actually start to run a folding protein program on your cell phone or on your laptop even when you're sitting at the conference and at the same time someone some rich guy or some like a research institution who has money can directly fund this process by giving your cryptocurrency because the cryptocurrency so entire friction to cross financial barriers and financial silos are so low that it's not becoming a problem if you're just doing like one dollar of work you can do one dollar of work and still get paid but you just couldn't do it today because of the financial barriers and that's kind of the thing that's just one thing that can you know immediately make me think of how this can help research we have to close the panel lunch so can I have your gum actually one two three hello if you need to eat the restaurant is to the left and to the left again thank you one two three four five six seven eight ten no one in Russian still doesn't understand I'm not good to see good afternoon good afternoon I'm James Little John so hello to all those that don't know me and I look forward to meeting those that I don't know already during the rest of the event I'm going to guide you through the data segment this afternoon and I just want to introduce this by taking up a point that John Tennant made about if we had all the things we agreed on all the things we disagreed upon and if we did that exercise my hypothesis would be that data would be the place that we could maybe achieve consensus and that would be the goal for this week he also mentioned that he would like to see more librarians in the community so I don't know if you can read my t-shirt but in the start of the year and our first speaker is part of a project called Damahub Dennis and it's top heavy with librarians in the caveat it is a small community so with that I'm going to pass you over to Dennis to talk about the Damahub project thank you and introduction from lunch how many of you guys know what Zhenki has been doing for living before he decided to dedicate his life to make science more open so you know Zhenki is a doctor but what kind of doctor is he and what he's been doing for a long time I'll show you a short video in 2 minutes sound on please hold on it's volume off where these arteries are what these arteries should look like and where there should be blood flow and when there's interruption in that blood flow it sends off an alert so the goal now is to get the clot out of the brain as quickly as we can if we cannot get this clot out of the brain the whole area of brain that you see here in green the whole area will be dead most likely so what we did in this case is use a smaller bore catheter to grab the clot this is actually the culprit for all his symptoms and now we have it outside the body and we have full restoration of flow hello how are you doing there sir good to see you so Zürnke is a radiologist 15 years ago I was brought into the Irish hospital with severe headache and the following day Zürnke's colleague Dr. Brennan stuck a wire into my leg brought it up to my brain and sprayed in each of four arteries contrast taking pictures this contrast filling up blood vessels in my brain then he called neurosurgeon named Mr. Ravlik and they looked at the pictures and they declared two things first they said there is not much brain the Irish and second they said that what there is a mess couple of hours later I had to bring back to the radiology room for another angiogram and shortly later I was given two options I had to decide the following morning whether they should do they should perform open brain surgery on me or they should try to fix to fill up the space which was created by bursted aneurysm through my leg with a coil and like in the situation like this you really want to make the best informed decision as possible but I was bound to the bed and the internet was still the mobile internet was still quite poor then so I asked three of my friends to do as much research as they can and all of them all three of them came back with the first thing they said that they hit the paywall so I am here to I am very grateful to to Yankee's colleague to introduce me to the problem of access to information and second I think we should all be very grateful to Yankee for organizing this event so I think he deserves another round of applause I was very lucky to be born in Soviet Union as a look back where all school books were free education was free and medical care was free but what I am trying to say here is that I do not remember the moment when I consciously decided when, where and by whom I was going to be conceived and that's I think true to anybody here we don't choose our gender our skin color we don't choose how prosperous our parents are so I think that like and I have Soviet idealistic views that each life should be equally valuable and I believe that anybody anywhere in the world should have access to vital information when it's needed like researchers, patients, doctors we live in the world which is driven by algorithms today so for example in China there is a social scoring system on trial at this particular moment and that system allows Chinese government to combine academic records with medical records, with criminal records with social media records with financial transaction records with shopping habits and to assign to each and every citizen a score so if you are buying a pack of napis you are carrying parent and your mortgage like the interest you are paying on your mortgage should go lower if you are buying a pack if you are buying a pack of beer you should expect that your health insurance premium could go up and if you are disagreeing with your government it's very possible that you won't be able to buy a train ticket and if you are on the train you should expect that to hear announcement that if you don't have a valid ticket or if you have if you misbehave yourself you should be recorded on individual credit information system this picture was taken a couple of weeks ago by one of my twitter buddies on Shanghai Benjib train so it's all reality today and if you think that any kind of legislation or your government will protect you from this kind of algorithms your dream and your not real because algorithms have no borders and companies which provide governments with algorithms they are at that moment refocusing from making money from utilizing consumer data to providing and selling information to your government to your bank and to insurance company so on one hand it can be used to help people to make to help patients and doctors to make life saving decisions on the other hand it's just a tool that can be used against us and when it comes to research data publicly funded how is it stored well it now now lives on over repositories around the world and then it advertised in one out of 30,000 academic journals and as we've learned from John Tennant early on in the morning only 25% of them are open access like this map approximate of institutional repositories they all of them have at least things in common first like institutions which built them invested lots of money resources to to help them secondly like it takes at least to people and $300,000 at the very minimum to run each of them and each each institutional repository has a single point of is a single point of failure and I believe that we should move from infrastructure for preservation of research outcomes of with science do not turn off into the system which cannot be turned off and how the system should look like I'd like to compare it with the road network the first sophisticated road network was built by the Romans during the Roman Empire times and they didn't ban the roads obviously but they were the first to decide that the roads have to be as straight as possible and the roads basically helped the empire to exist for 500 years and it became roads became arteries connecting the vast network of the melting pot of cultures, religions and institutions they served the purpose they allowed to move troops from Portugal to Constantinople as quickly as possible goods delivered people were moving so many of us here I believe want to build applications some kind which will improve or which will make the science more open I see applications as vehicles which go on the road and each piece of gravel on each stone which goes into the road can be seen as a research object but before we are building this vehicle which will be using the road I think we should have some kind of idea in what kind of condition this vehicle will be used will it be used because unless we know for what kind of environment the vehicle is built we may end up driving tractors Belarus on German autobahn and drive from Barginis on Russian Siberian roads there is nothing wrong with tractors Belarus I have to say they are probably the most unhackable tractors which still remain let's stick with Lambos how many of you want to build killer apps yeah you? no no we don't need killer apps we need Lambo apps and but Lambo apps I mean applications which Lambert Heller he left he has just left Lambert Heller and his colleagues academic librarians can advise their researchers to use when they come and ask him what they should do to comply with increasing demands from funders from European Union to comply with data preservation policies and to make their research outcome findable, discoverable and reusable for generations to come yes, actually Rachel Lamborghini like when he started from building tractors and then he moved to supercars but like if and Lambers which I built now they still able to pass each other on the road because when they build their road network decided that each road needs to be at least 4.2 meters wide and we're still building around the world roads which are as wide as this and if you look at the cross section of each road we create a compartment and you fill up with gravel and different sources of material put on top and then it's maintained and lasts for many years so in the same way we should see digital infrastructure for preservation of scientific data and vehicles which will be on top of it and they will be using it so there is a couple of people here in the audience James and Karman was participating in our events and Zhonky's we've been thinking for what cross section of infrastructure for preservation of scientific data should look like and it all starts from from protocols we need to decide what works and needs to be preserved so we need to know what is like what kind of what is data object and what kind of metadata we want to be preserved we want to use peer to peer open the license protocol which allow to address each and every research object based content there is a number of groups working in this space at this moment IPFS has been mentioned already which is interplanetary file sharing system SafeMate is working on develop something similar or that project for example and we know for sure that the system which is works to be created needs to be decentralized because otherwise we come back to the system which has a single point of failure which can be switched off intentional or not and we need to reuse what's already useful such as digital object identifier or cheat ID services go on top of it and applications so yeah let's reiterate on it there is a number of groups now deciding what research object is we need more academic librarians like Lambert to be included in the conversations like we are having here distributed like openly licensed hypermedia protocols which allow to address those digital object by their content IPFS needs to be like we see it as a solution for creating this distributed system and it has to be governed so in the way that we can audit and verify on what kind of system and surely you need to find stuff so like those objects need to be made discoverable so I'm inviting you here to help us to develop and to participate in designing the system which like to design governance is very important because people who are using the system have to have a stake in it and they have to be able to influence decisions which will affect it so if we want to use if we want to use if we want algorithms to benefit not only governments corporations and banks but them to be employed to help researchers doctors and patients to make important decisions we need to create a distributed system which allows us to to make this data findable, accessible, interoperable and usable yeah so there is a number of groups trying to resolve it to look at it on different levels there is for example Freya project which is funded by the European Union it's three years long there is like a protocol labs working on IPFS which created IPFS and they're trying to resolve the problem with like those identifiers needs to be persistent and immutable which is still an unresolved problem European Union has the European Open Science Cloud which needs to be included into conversation and then it's intercontinental because in Europe for example there is a research data alliance very active in this space and in the United States there is data together and I don't think that both talking to each other so all of them have to be included in conversation somehow before in order for us to create this infrastructure where we can drive Lambos thank you Dennis so we're now open for questions if you put your hand up Mike will come to you I'll just maybe ask quick one Dennis you do a weekly discussion forum and you've done events to find out about where you meet up yeah we have a weekly call every Tuesday at one o'clock you can find information on Gitter or about it and yeah choose the call it will be the best way to contact you can contact us individually and we'll put you we'll let you know what's going on okay thank you very much so we're just going to take a small break because all we all know is data scientists we don't collect data we can't do the data science Alexandra is going to make a plea for some data from you hi just a quick announcement so my name is Alexandra I'm from the blockchain and society lab at the University of Amsterdam and together with and other researchers at the Netherlands we're doing a survey that maps projects that are involved in the blockchain for science community what are the challenges what are the limitations and the potential we have an online survey that we would all like for you to participate I can also do a quick interview with you later in the day or tomorrow so please come find me whenever you have time it'll take maybe 10 minutes thank you and one other omission there was meant to be a poster session during lunch but due to running late all those great conversations over lunch we'll do it tomorrow so our next speaker is Conrad someone that's new to me but this internet is a great thing so I did a stalk on him and I think he's at the co-face of data science he's got his public keys on his website and all his data well organized so I'm looking forward to hearing more about what he's doing okay thanks I would like to talk a little bit about how we can hopefully generate open knowledge based on closed data and what kind of new deals are out there to make this happen smallest claim in this perspective or in this regards is I will mention some companies later on that seem to have solutions regarding this I have no connections here and I'm coming more from the perspective of the bioinformatician who crunches a lot of data on a daily basis and enjoys doing this in the open so as an open science enthusiast and John mentioned this already in the morning and he actually laid the foundation for this talk in a way in science everything data source code and clearly in the end the paper has to be open and the others would not be good scientific practice I like to avoid the word open science often because as John also already said this is just pure science that the foundations of our scientific process is openness and there's a small but whenever I give this workshops regarding open science and how we can implement this somebody raises the hand and says but well I have a computer that is linked to personalities that is linked to patients so there is a higher good sometimes which is called privacy if I'm a patient I have cancer I would like maybe to donate my genome data for example for research purposes but what I do not want is that this is somehow linked to myself and in principle this is only one we have a lot of data that we should share but maybe should not share because it has an implication on how we can live so behavior data everybody or many people have fitness trackers for example that track behavior or what am I eating all these kind of things can be stored and can be used in science to see general trends socio-economical status is also something that in principle is can be a piece of research so you can collect this data and try to make scientific statements out of that but as an individual I to be honest would not like to have this in the hands of other people medical records we just saw the example before by Dennis that you basically sharing this data can be useful for the research process for researchers but for the individual this might be not so beneficial at least in a certain amount of time and if we come to the core of ourselves the genomes or axons or at least some snips and these are maybe some biological expressions but I think everybody is aware that we carry basically the blueprint of our body in us and every cell so the genome the DNA is an important description of who we are and well how we develop and how we live today we have actually technologies making this easily accessible this is one chart that you find very often the first human genome costed around 2.7 billion US dollars and took 10 years and this was then available roughly the draft in 2001 and when you then started to sequence a new genome it just costed 100 million cheap in comparison today and this is due to different technologies that arise roughly in the mid-2000s today I can sequence a genome in roughly one or two days for around $1000 this is definitely a game changer and I'm pretty sure many people are interested in having access to this data for their own purposes for medical reasons for example in order to have personalized medicine and this is a very powerful tool that will definitely change how we can do medicine and how we can do science and then we are not only our body here but we are actually an ecosystem and we're carrying a lot of bacteria in us so the so called microbiome our gut microbiome, skin microbiome all of this can be tracked today again sequencing technologies are actually helping here and also this is saying something about me and also this can be something very interesting for researchers and then anyone would like to even connect all this so if you know how people behave or if you have certain traits how they are linked to the genome this is then the interesting question that for example G-Bus analysis can solve so in principle as a researcher with a lot of interest in this type of data as an individual I am actually not very interested in sharing this because this gives a lot of weak points maybe to others so scientifically speaking we have a lot of interest having these data of a large population and it will dramatically impact how we can science, how we can do research to do that but on the other hand this can be really a problem if this kind of information leaks and is accessible because this can lead to systematic discrimination due to political, ideological or even commercial interest maybe the health insurance is not taking my contract or I cannot sign a contract because they know I have a certain disease and I have to pay more for that to take another one and this is kind of questioning our solidarity system maybe at some point people are discriminated because they carry a certain allele of a gene so in principle there are good reasons to make this data open but there are also a bunch of good reasons to not make them open so we have clearly a moral dilemma here should we protect our rights or should we push the scientific progress and this was mainly for medical data but clearly this kind of situation is also in many other fields for example financial data of organizations you could do really make interesting research on top of that but the individual organization like a company might not be interested in sharing this energy consumption of devices for example it would be also engineer devices differently location data of vehicles all these kind of data from different domains have a similar problem they might be very interesting if we have a large population where we can have access to but it brings issues for the individual there or the organization so how can this be solved so is there kind of the possibility that we can generate an open, ideally open knowledge on close data can we have kind of black boxes that we can maybe see the full data but that we can at least reproduce if somebody claims something that we can go back to the same blocked or hidden data run our algorithm and get the same results can we maybe train machine learning models on top of that data and use that for analysis later on or at least can we make predictions on top of this close data that then can be confirmed in different ways so using this more as a hypothesis generation machinery how is this done currently just an example Genomics England is a state-holder company that aims to have 100,000 full human genomes which is huge what they do currently they have close data centers where only certain people have access to remotely and they can run their algorithms there and only the results leave this via an airlock similar approach is the so-called personal health train they have these data stations similar to this so basic data centers where you can push in some algorithms some more programs actually and you get some data out so again both of them have locked systems and you need again as always you need to trust these instances and trust is something that is not always well-earned for example 23andMe a company that brings genome information SNP sequencing or SNP information to the broad population and then they sell it so you went there you just want to know a little bit about your own background and suddenly they sell information to others once again this is nothing you can change if you lose your key, okay if you lose your bitcoins, okay this is your damn genome you cannot just get it back well there's genome editing but this is something far away and this is by the way not only your genome this tells a lot about your family as well so this has huge implications and this is really a catastrophe so there must be better solutions and there are so I said with this question in mind I looked around a little bit and tried to understand where we stand in respect to that and there are blockchain based decentralized data market places that try to exactly help here the promise is that the data owners so for example if I sequence my genome I can put it somewhere and try a full control about what of that is shared and with whom that is shared one important thing is also kind of a standardization of data and what the let's say the people who want to consume the data have is kind of that they can incentivize to get more of their data and there it becomes already a little bit critical but in principle a genome costs $1,000 this is still too much for many people but if you put into such a system into such a marketplace information about yourself maybe you have a certain disease maybe you're healthy I don't know but if you put this information into that marketplace the data consumers can contact you indirectly and tell you okay if we get your genome you will get this and this token that can be later on be traded but with this they can have an incentive or given incentive to sequence certain people or to get more information doesn't have to be the genome sequence can be also other stuff but with this the idea is actually to promote this accumulation or this collection of data in a standardized way in an anonymous way and give also the power to the data owner again and this to be honest sounds very interesting for pharmaceutical industry this is very interesting because they can have this traceability again if they say okay we have a bunch of patients here we do this and this try on them and we get now this wonderful results and we can sell our medicine here but under the hood nobody can prove this with such a system they can always say okay here's the data if you run your own analysis on top of this you should get the same results and this would look then very simply like this you have the marketplace the data owner give access to the data to a data consumer and return get a token very simply speaking and still keep as said all the rights all the power over above their own data there are certain underlying concepts some of them were mentioned before fully homophobic encryption in there and as far as I understand doesn't was not really well implemented so far multi-party computation might be a solution basically you break down the problem into smaller pieces and an attacker would have to have control over the whole network they built on certain hardware concepts trusted execution environments like SGX from Intel there are a lot of these things out there at least as white papers discussing this and said this would look very roughly then that the data consumer ask for example for certain data might find it already in via the blockchain sorry the data consumer might ask for this might find somebody who offers this already or motivates data owners to contribute their data the data importantly is stored off-chain so is outside there and is not stored in the blockchain and then you have these secure compute nodes SGX for example and the data owner allows the data consumer to have access to the data to give it basically into the secure compute node and only gets in the end the results of that computation so rather elegant but also rather complicated system in my opinion and there are numerous protocols, providers that have kind of a general purpose solution for this at hand, ocean protocol we will hear right after me I guess, enigma protocol they have the concept of secret contracts basically smart contracts but in these kind of encrypted environments or in these trusted environments the key in protocol from the ASIS lab and open mind clearly with a focus on machine learning although I think the ocean protocol also has a focus on this so there are different potential providers of solutions in this perspective and they are not limited to a certain use case but are rather broad on the other hand we also have kind of more specialized providers coming from healthcare and they come with these kind of concepts so very elaborate it is already Nebula and Long Genesis so Nebula has to please keep in mind this is done by George Church who is a big driver in this genomic field and strong person in that field there is also Lunar DNA I am not sure how to pronounce this PHAROS encryption and all of them offer solutions basically that you are not unfortunately not yet offer solutions but they tell that they will offer solutions where you can either give health data, health records or even genomic data and Nebula is even working together with a sequencing facility in order to generate the data to store the data and then put this into these private pots that can then be managed via a blockchain approach so there are already a lot of people in the boat who offer solutions that sound at least interesting to me but now the question is will these data market places really improve our science but I would say maybe and this has definitely potential and I said as a bioinformatician this is kind of the paradise for me if we have access to this kind of data this would be really great and I think it's a trade-off between openness and I said I am a very strong open science proponent and I still always have these debates and they could be stopped here because we can say here is a mode where we pay have kind of a trade-off we pay off a little leave a little bit of openness away but instead we have access to lots of data and this will push our knowledge dramatically in my opinion but currently maybe I'm wrong and I'm very happy if somebody can correct me here I see only a lot of white papers and for this I could not test anything here maybe I'm wrong and maybe somebody can do a small demo later I'm very happy to see that I completely agree that this should not be out too early in this case once again this is basically your genome and unfortunately the discussion is happening mostly by companies and not academics so thank you Zunke for organizing this because here is a strong proportion at least from the academic field and this is important I see a lot of potential here and it would be a pity if this is ending up in the protocols and proprietary solutions and we are out of that again and I mentioned this before it's good that it's not too early out there in my opinion because once your genome or at least snips of that are out there you will not get that back so this is really crucial that we have a rock solid solution as I said with bitcoin in the worst case yes you lose maybe a large fraction of your money but your genome you will never can replace and if you have a disease and for whatever reason somebody makes this accessible and this will be out there forever and also for example your children or your family so this can go back in your tree of life in a way and there are also other issues that even if you have not direct access to the data we can still use certain tools to well de-analyze the data there is a paper from 2013 where they used certain traits and could link this again to last names this is again a crucial thing and it's too precious and I made this rather simple with my little drawing how this should work but the complexity of these systems is dramatic as I said this is a multi player solution you have a lot of things to keep in mind here and it's very complex and this means it might break easily you might also have problems with different legal systems again we had this I think several times before it's clearly it's a global thing and nobody can forbid me to put data there but maybe in the end I have some issues if I want to use the data and what might be also an issue is that we incentivize now people to contribute their genome but they are actually not aware of these problems that they say ok this is good quick money for myself I put my genome I put my behavioral data in there and then they afterwards recognize that this is a problem that they cannot get that back so education is needed as crucial as always thanks John again education is key and data is as said stored off chain and this is kind of my opinion outsourcing the problem to others and this has to be solved I read in one white paper for example they suggest to put the genome then on Dropbox that's ridiculous this is the most precious thing who would do that I wouldn't at least no well and who makes sure that the claims that people write for example put into the blockchain order to be found by companies incentivizing them that they are not wrong if I'm a poor person I have depth and I know that if I'm belonging to a certain group my genome is sequenced and I can give this and get money for that maybe I lie when I fill out these forms so this is my opinion not clearly solved bottom line this is super promising as a bioinformatician this is awesome having this access to data and as a trade off between openness and privacy but I think there's still a long way to go but we should go it we should try to get it and see if this works out for us so what are your questions thank you very much yes please thanks for this presentation you mentioned this in the companies like from George church and so on I'm a bit critical about this I wonder how much this is not creating just new silos because they are actually to my understanding all ICO driven projects that just were there when you could still make money with this last year they were quick and George church is always quick doesn't mean that he always has the idea by himself because origins then might prove that many of the ideas others had before but he's very loud that said okay now it's there but I think just it creates new silos and I don't think actually in the interest of the this movement that we are trying to I completely agree with you and this is why I also suggested we academics have to have the discussion because it's already ongoing there and we have the risk that we are outside of this and that this is just a big playground for pharmaceutical companies and not for the general public anyone else no we'll keep the good time thank you thank you very much a year ago I sat down with Dimi in a white board and some because I was watching I think asking what language we were speaking so that was a year ago and I think from that the ocean protocol emerged in some shape or form so I'm looking forward to hearing where it is and where it's going over to you Dimi Dimi, sorry fantastic hi everyone my name is Dimi I'm from ocean protocol I've been working around decentralized data for a few years now and we started up with looking at intellectual property and creator rights in a scribe now we moved on to how can we create open source decentralized databases like big chain DB and it came down to something that's now ocean protocol where we're looking more at intelligence data without humans without consolidation is not much worth so we're looking into public intelligence networks incentive systems around those and it's early days for many of these things but the paradigm shifts that we're employing are interesting and promising and at least it's something else I have a background in machine learning for let's say micro electronics modeling and I used a lot of predictive models to check what's the actual performance of such designs of micro electronics into the real world and some of these things would take like years to compute taking into account all these process variations and stuff so we would make models out of them, accelerate and we always were looking for a better model but rather just looking at more data would have given us the same results without basically being skeptical about is it a support vector machine a neural net, some Bayesian network so it's shown that if you just feed more and more data to AI it becomes quite powerful and this data revolution has been starting for 15 years and there's a few entities in the world that are really good at it so they get most of the benefits just to give you an idea we're working around something called autonomous driving there's this mobi platform tries to pull a lot of car manufacturers fleet managers you could say anyone with a dash cam and it's all about looking at what's the amount of data required to create models that are safe enough to employ into autonomous cars and it turns out that it's about 5 billion miles maybe more and that would take maybe 40 to 50 years to acquire for a single company so pooling between companies might be interesting so data pooling by itself is very interesting but then also opening it up for an intelligence network of data scientists is even better so we come to a point where we see that there is a lot of data out there but it's locked up and only few enterprises have also the data scientists to consolidate that data to extract the value from it there's a lot of AI startups typically coming from big companies but then they don't have the access to the data so in the middle there's just a few lucky few which obviously sometimes crew it up or they well you could say don't be evil it's something from the past already and yeah data is a lot of value and a lot of money and it leaks and it breaches and yeah we kind of got used to all these things but I think giving a more equitable model for this is more sustainable for the future so that's what we try to implement in the protocol because well it's an open source community it's not really an enterprise we're not out there to create money we're out there to make something that's sustainable something that well can give you an alternative to existing data monopolies or AI monopolies and it's all about democratizing access to data and AI or intelligence some core principles are self sovereignty being the owner, the controller of your data assets also attribution and provenance and of course privacy so trying to disintermediate between these two worlds doesn't only need something like monetization in the middle but also something about the commons and commons is something we tend to forget that it still exists however if we're working open source or in open data or in open science then you could say the commons is the open source code maybe that review everything related to digital commons and media art but it's something that companies don't really tend to implement sometimes they create an open source project in a service layer on top of that and that's quite nice I think that's an incentivized commons that's basically one of the things we like to think about so rather than siloing resources into centralized economies we're looking at pooling resources decentralized in communities and so one of the first things we did one and a half year ago was creating like a data sharing tool it was about data access sharing and this was a project together with Toyota and well it was more exploratory looking at how can you open up or connect multiple data providers without actually leaking their data so one of the big problems is that companies want to share data but they don't want to have their data escape so as in the previous talk was mentioned is that is possible and you can use technologies like multi-party computation or homomorphic encryption or trusted hardware but still you're relying on a lot of components and I think if you look at data sharing it's not the sharing that you want it's the consolidation of the data so typically you're looking at how can I prove that I run somebody's algorithm in my data center and how can I prove that I actually did it and that I actually run the algorithm on the correct data and can I also deliver a cryptographic proof or some form of trust that vouches for my actions so many of these things were encapsulated in this project and that's kind of the start of Ocean Protocol we're working with a company in Munich who's called Connected Life and their privacy is of course well it's health data it's health monitoring data and there is very important to look at how can we preserve privacy and negotiate privacy and how can we make sure that there is no leakage of the personal identifiable information sorry I'm having some problems with my... yeah, yeah, I don't know how it happened cool, alright give me a second okay so Connected Life is a company in Munich they're looking into DNA and other types of things mainly related to Parkinson and all the data they can gather is useful but they don't need to know the source of the human they just need to know the data around the data so that they can have data scientists exercise their algorithms make better predictors and automate the process so looking at these things then I think things like well you could say a fund for data science maybe getting a hard time on my press maybe well just looking into another use case here we have something called the universal recommender and think about all the data that you use for labeling what you like, what you don't like the suggestions you get from Netflix, LinkedIn all that personal preference and opinion is now somewhere scattered if you would only have like one minute of your digital life on a daily basis what could you have for an AI assistant and saying like what would be the most interesting thing for you to do now what would be your most preference action or best service to connect with so can you gather all these personal preferences into your own digital software and look at my personal universal recommender could be trained on humanity but could be personalized towards yourself think of it as a form of AI assistant or coach learning of all the actions you do but staying on your control on your software access so all of these things are quite promising but then why would you use a blockchain to help here I mean it's about self sovereignty it's about privacy preserving tools a blockchain is just something that connects these things and I have like I think I have three versions of a blockchain that explain what are the aspects that we think are interesting to include in this data sharing economy so first of all a blockchain as a chain of blocks which is all about provenance and provenance of things that happened in the real world claims, proofs and they have consensus power this means like the proof of work that a blockchain does or proof of stake of other blockchains and sometimes I could just compare it a bit like carbon dating it's basically a forensic tool that allows you in the digital age to say that well somebody made this claim at this point in time and it's being agreed upon by a majority of consensus so in notion protocol our applications are data service supply chains they're basically a combination between data algorithms and compute and this means that an algorithm can run on data in some suit environment and then store the result for inspection or maybe for annotation and what we want to do is well we create time stamping processes in the middle that actually say that well this person actually delivered data this entity delivered algorithm and this compute did its job they combined the data and the algorithm to store the results somewhere else and all these actions get recorded as a provenance tree on to a blockchain so we're not only looking at single providers but for each of them like a full network that you can say well it's an inter-service network it can combine any type of service for data or algorithms or compute into a full network so you could always choose what's your what's the cheapest what's the most decentralized what's the most privacy preserving best encrypted what have you another way to look at a blockchain is a world computer and there we have smart contracts running as kind of unstoppable codes on to a world computer and for us it's about creating agreements and agreements around computation is well where does actual computation is going to take place is it on my site am I going to download the data or am I going to send out my algorithm towards a trusted provider towards the data owner and we have to have this negotiation and that negotiation goes into the conditions of a smart service agreement or just let's say a smart contract containing a service agreement so this is quite interesting because it gives you a bit of mutual protection between sites if you're a data consumer and you say well I'm only going to pay if you actually show good behavior on let's say good behavior is running my algorithm on to your data set whilst the data owners could also say well here's a little bit of warranty that if I behave badly you get basically part of my stake in the game so here you can play with negotiations and agreements between parties and I guess if we're flexible here we can encompass a whole range of use cases not only look at privacy preserving but also public data now data science is a bit of tricky what we have is that we have to combine at least three ingredients to get intelligence data and then human work in an algorithm and a compute layer now obviously not every configuration is perfect so private data doesn't want to leave no data escape but big data also doesn't really want to leave because it's just too big you can't push it over a wire sometimes there's this thing called the FedEx bandwidth and basically says at some point if the data becomes too big it's more cheap to take out the hard drives moving the FedEx truck across the country than sending the data over the wires so assuming that big data doesn't want to move the algorithm to the data side and that's something you'll see in a lot of hardware manufacturing processes as well NVIDIA is optimizing to put more compute facilities around the data storage site etc so this is your negotiation patterns that you have for as a service agreement well it's a smart contract has three parts the service that you can detect on a metadata store then you have conditions which is cryptographic challenges that need to be solved and then you have a reward section for payouts and the payout is according to the service quality that's being validated so each actor in the system might have its own conditions to bring to the agreement and its own terms of payment so creating a flexible platform for the ocean contracts that we're providing and many of these conditions aren't ideally they're cryptographically secure but sometimes they're more subjective and then you have to have stuff like human creation, dispute resolution albeit legal or not one of the use cases we have and we created an infrastructure around that is where there is a secure sandbox at the data providers side the data always remains within the data provider and then data scientists can submit algorithms to this data science sandbox and that data science sandbox generates proofs that it actually run this algorithm on a data set and those proofs are the ones that go into the ocean network and access control for allowing the algorithm to go into the data into the sandbox is what's happening in the service agreement we're creating a few interfaces for data discovery but also how you would use ocean in a Jupiter notebook we just want data scientists to use their own tools we just have this additional superpower and that means we'll connect to more data sources discover monetize data what have you one of the things we're looking for that we've also been working for a lot is how can we signal relevance of data sets and there is this interesting concept of creation or tokenized creation that allows people to basically lock up some portion of money saying that well I think this data set will perform well in the future it will become popular so I'm putting up a bet on this data sets popularity and if it gets used more I get a bit of interest from that bet the last version of a blockchain is an incentive machine where we're looking at how can we have a blockchain that rewards people with minting or creating new tokens and assigning them to people with good behavior one of the earliest examples is for example looking at the bitcoin network here people have been adding compute power to the network hashing power because they got rewards for it they got bitcoins and what you get now is this huge supercomputer that basically has A6 custom chips has people operating them in mining farms and there's a lot of people acting around this network just to get that bitcoin reward so you could say this is a quite effective incentive machine now it's also a bit of a dangerous incentive machine because it only has one incentive that is add more computers to the network secure the network more and more and then you can create something like well here's a paperclip optimizer showing that maybe we should be more careful in designing these optimization functions or these objective functions so what would it be for open data, open science I think there's a lot of debate that you can do about incentives for open and common science what would be good incentives, what would be bad incentives I don't think a single objective function would fit but looking at the core values of this network where there is self sovereignty there is attribution there is privacy incentivizing maybe relevance and quality openness so everything that can be kind of proven or at least vouch for in the real world can become a lottery ticket to a reward function that's an interesting mechanism because then you can earn tokens by having good behavior and use those tokens to consume more services or get a bit more governance or control in the network so if I look at behavior in myself I have like like most humans we have two actors in our brains one of them is a rational decision maker the secondary brain part and then we have this primary monkey in our brain which is all about instant gratification and those two have to be taken into account when creating an incentive system now for ocean we have something called network rewards it's basically a big portion of the ocean tokens are locked up at least across the operations of the network towards what we think is good behavior in the system of course what is good behavior is subjective and it's governance now for us our initial design function is we want to maximize the supply of relevant data services data services, data access storage algorithms, compute creation it's all part of that so if you can prove that you delivered one of those services in the network you get a lottery ticket and every 10 minutes or every hour you get the chances that you get drawn from this lottery and you get tokens as a reward this means that governance becomes more and more important because it's about how you steer the network function the objective function in the network and how we're thinking about this is well there will be a form of global network governance talking about protocol updates but if you have then specific let's say data pockets or knowledge tribes then they have different missions and visions they might also have different types of incentives, tasks bounties and things to be solved so grouping these things into more clustered tribal systems we call them but it's basically communities is part of our design as a last slide I just want to think about a few things that might be interesting for discussion so for science and research I think provenance creating trusted knowledge graphs, curated knowledge graphs maybe think about if you create a dynamic paper in the site and if you click on an experiment you can automatically see the data flow from previous experiments until the source public funding and rewards currently it's institutionalized but I think many people would benefit from a kind of more open funding system governance around research projects publications what gets accepted into what not communities but also just signaling of emerging properties and locking up a commitment saying that if this gets accepted as a project it's actually going to release my signaled funds hence promoting more and more emergent problems and things that people care about and not only like institutions or governments so feel free to have a chat with me maybe you can flesh out one of these things yeah that's it there's also well there's a lot of if you want to know more about ocean there's a lot of things you can do to help or to just check out some of the code we're doing we also have a big bounty system we already completed a few interesting ones but you can also just suggest a bounty saying that well this would be cool to do with ocean protocol can you guys let us with some tokens or everything related to the bounty infrastructure that we're using so that's me if you have questions go ahead so Conrad promised us it would be a complex world but thank you very much for a well thought out explanation of the inside workings I think I've seen a hand up at the back thank you very much for this idea and how far are we away from playing around with this so I mentioned before that I couldn't find really something that was so really useful where we actually could put something in practice how far you're away from this so let's assume I have a small use case an academic small use case I want to run that can we do this tomorrow or do we need to wait where are we standing here I think you can do a lot today we have a thing called fit chain which has the on-prem compute with containers so you basically what you do is you put your algorithm in a container you ship to an on-prem compute and those two services are enabled in two weeks we'll release our second version of the test network so you also have like you don't have to care about running Ethereum instances or nothing like that just and then you can plug in some of the Jupyter notebooks have a few modules around that as well yeah I mean just check the GitHub there is a lot of things popping up every day so that's cool thank you thank you how do you go about preventing like the rich multinational organizations or enterprises dominating the open source systems yeah that's a good question if you create decentralized systems and then you have a few whales entering and then they basically centralized this stuff again well there's a few ways you either have different incentives and saying that for people to participate in the system you have to make stuff for free and open for the commons and that's already deterrent for many multinationals other ways could be saying that well we have a tribe and we set up a local governance system and in order to become member of this you have to be part of an open public society rather than part of a company so what we want to avoid is any type of threshold for people it has to be a permissionless system as a bottom if you create the internet you're also not excluding big companies because they basically build it so the protocol itself is agnostic local governance systems could help choosing what incentive schemas you want and what not thank you for your presentation at some moment you mentioned a secure sandbox as part when the fore notes that actually execute how do you ensure that there is no data leakage at that point and if this sandbox imposes some sort of constraint on the complexity of what you can run inside them I think you summarized the trade-offs really well we've been looking in things like SGX and NPC and I must say SGX has a memory requirement that's just not feasible for big data I think it's 265 megabytes you can run in the enclave and that's just not going to work having no data escapes, for example if you have a one nearest neighbor model that you send to and basically it maps out the real data onto these model parameters and sends it out again that would be a kind of an attack through the model I think just having common practice in saying if you are sending data or allowing access to data in your own secure sandbox make sure it's minimized, make sure it may be already clustered or aggregated what you can do and a few of these things that we are doing is curating the templates of what are the typical types of models that at least enforce an aggregation function for no raw data escapes but more seeing first make sure that the end layer of your model at least has an aggregation function that it doesn't also have the raw data points exposed in the end I think it's the responsibility and also the right to choose where your data goes and how you treat it at least these sandboxes are running on the provider's side so that's where you can do any if you don't want to leave your premise in the end then you just block it thank you very much and I want to quickly thank all speakers for their thoughtful insight on their data work thank you so I'm going to hand you on to the safe hands of Carmen for the panel but before I do that Sonka has reminded me that tomorrow there's a chance to do a 10 minute open talk, comment review feedback demo so if you're interested in that speak to Sonka or see the website and with that we're going to organise a panel led by Carmen, thank you to start actually I thought my role was just to sit here and look pretty but I guess I have to ask some questions too so I guess before we start so I'm actually a researcher I tried to build also some kind of data infrastructure for computational chemistry and it's a difficult problem so infrastructure is not a sexy problem and actually nobody really cares about it so the question is like how to get money and that's also how I ended up here and looking at decentralized solutions so I think I would like to say that I'm not also particularly how to put it I think decentralisation is probably more important than blockchain because science is fundamentally decentralised activity so we need to I think develop infrastructure which supports this kind of effort so it doesn't matter if you are from Brazil or Max Planck you should have ability to access data from anyone in the world so how do we do this and I guess what are your thoughts about that who wants to start Dennis? Hello, hello, yeah my interest in in preservation of scientific data came from interest in open data so like in Ireland we started to when we introduced the Irish government to the concept of open data there were exactly zero open data sets and then like probably in 2015 when there were a few thousand data sets we asked the question how do we know that first this data needs to be trusted and secondly how do we know that it will be available tomorrow and we started to think about how to employ those distributed technologies for preservation of this data and coming back to my road analogy like I think the infrastructure has to be publicly funded I don't see because the projects have the beginning and the end and if you go from one funder or one grant to another as soon as you get one grant you start thinking how you get another one to keep it going and that's not sustainable so building anything starts from standards in our view and defining first of all what needs to be preserved and what is valuable in the future that would be a good start how to do it it's an open question because there is a community in Silas talking like one community will discuss research object others will work on protocols and experiment with something I don't think that those blockchain communities have enough librarians in place and scientists and practitioners and at the same time yes there is not enough people from a technological background to go and talk to the people who discuss research objects and protocols also I wanted to say if anyone has questions please just also feel free to ask because I think we can make it more interactive like that if you have any suggestions or if you are thinking about anything otherwise I can continue and in a way it's funny because we just had the discussion at dinner so definitely here are also some of your ideas that we discussed and yes infrastructure is unfortunately not sexy especially as you said actually establishing this is even easier but then the maintenance this is actually the tricky part that is hard to get money for and luckily I think there are new things on the horizon that I think more long term but also standards are critical and why it's not sexy is because it's effort and as a scientist, I'm a scientist myself working in an infrastructure institution now I see the issue or maybe the solution there that we have to make this infrastructure thinking sexy again by providing cool tools currently people cut out images, put them into PowerPoint and store this as their data and this is ridiculous this is just generating breaks in the scientific workflow and if we can convince people that these cool tools help them to make their research better, easier, faster and more reliable then they might gain the interest and maybe also their money but they tell the funders and by the way I need more of these cool tools in order to make my research better so in the meantime do we start first making these tools or actually mobilizing people to actually ask funders to support making all these tools it's a chicken egg problem clearly my approach would be start with cool tools that you build from stuff that is around and sometimes you just have to put stuff together just to show if you do it like this you save already some time I hope so Any ideas from yeah I mean there's a lot of cool tools already that exists like think about the Kaggle community and all the bounties that are open there and the challenges and basically working on honor and rewards functions okay I guess then let's reformulate the question how do we make researchers use those cool tools well I mean popularizing these things in university shouldn't be too difficult to give them a bit more time or make them like what if research bodies or funding institutions create such kind of challenges for people to solve but that's kind of the problem because it is difficult because nothing really changes or it changes very very slowly so some cool tools have existed for many years and I think I gave an example of Google Docs so Google Docs exists for many many years and still I personally got like version 12 of a word file then version 12 and then initials who has changed so we don't even use Google Docs to actually write papers so I think cool tools are developed in the outside world but we are kind of stuck like close to the I don't know paging I remember like I did five years of research and indeed I got those version 12a from word file in email and then I had to change all the styles and it was a mess and then you open it on your windows machine and it was a no we don't have researchers don't have windows but I did discover bitcoin when I was researching and other type of cool tools or emerging things so yeah I guess that's more inside of the researcher his ability to become more he or she to become more productive or use tools that are enterprise grade or I don't know yeah have to change the mindset of a researcher I don't know it's also a legacy problem I think because yeah there's no one that always brings us up here I'm just let's play a thought experiment you guys are all researchers you get into your office the first day you need to do a bunch of experiments you're probably going to spend 14 hours on those experiments what are the actual problems that you're having right now to your life for you to feed your family so it's funding right what do you need to get funding if we go back to first principles about all the things that you do every day as a researcher you all were researchers at some point don't forget that then you find the solutions then you know what the actual problems are and then you can actually find the solutions getting a researcher to change their mind it's not hard but what's the point if I'm going all I want to do is look at collagen forever that's the only molecule that means the most why do I care about blockchain well that's exactly the thing so you shouldn't care about all these things at all but you have to because at the moment there are no other tools than the existing ones so that's why you have to think constantly about funding and publishing because that's how the system is designed so we need to change the system but the question is how and we need to change exactly if tomorrow let's say we don't have to build anything new nicer essentially so that you don't it goes back to actually making people nicer so you don't I don't know publish crappy papers for example that also so you don't need to so you don't have to publish as much you don't have to maybe chase so many grants if grants will last longer than a year or two so it's also about how do we support research and the truth is we don't so I think this conference is about actually finding possible solutions like how can we support research and not in a way like what can we do to fix the current system but my thinking is like what can we do using this new technology to actually make something new and different and actually more aligned with you I mean personal values of the researchers which is mostly like curiosity and like that yeah there are people who are interested in college and for example and why not let them to actually spend their lives researching college and but you can't do that doc you have to research that and then few other things that are that you know that will get funded yeah well just to tap into this a bit what I figured is that these decentralized communities is all about the communities themselves and what blockchain brings is not only just a community of messaging it's also a community of sharing actual value and redistributing value and getting provenance so the actual tool is community building and if you're a researcher that doesn't care about what other researchers are doing just go for your next publication then you're probably going to have a hard time anyways so if you can live in a college in community where you share insights and issue mutual rewards or whatever you have I think that's basically the start no community thinking there is a solution researchers work really well if they have a mentor and that's not a new concept but maybe the mentor needs to be the person that has that link to blockchain so the researcher doesn't have to get involved in that aspect there's somebody who takes that away and does something with it so you have a bridge well that's a really interesting comment so something that I when I look at all the solutions in blockchain space there's a lot of incentivizing of peer review which I think is a futile effort because there's no need to incentivize peer review people will gladly criticize you but mentorship for example is very important and nobody is looking to create incentives for people to be good mentors and it's something that will first well essentially because researchers are so overwhelmed and something is going to give and this is one of the first things because you are not really rewarded to be a good mentor so a lot of researchers actually or young scientists are not really being mentored very well so that's also one of the things to look at but in terms of I guess data I guess that's again a different problem so it's all kind of connected but how to solve everything in one go I don't think it's possible so we need to try and experiment I think this is all one big experiment so we don't also have to be overly critical because it's very young technology and many things will fail I guess as well but maybe something good will come out of it as well to have a chance we can create many technologies but they have to be used and for them to be used it has to be the solution have to fit into researchers workflow and you shouldn't think about what blockchain is and how it's saved it's not your problem you want to build career and to feed your family and to pay you like to buy a house whatever like you want and it should be possible to do on data attribution and like right now there is increasing demands whether from funders or from European commission for example if you get more than certain amount of grants or in of resources for research half percent of it needs to go for data preservation and each and every proposal has to have data management plan so that's one incentive how the solution and how the tools will be built and how obviously there is like different disciplines and different tools required but it all needs to be built on like all those tools needs to be built on protocols and on they have to be interoperable right interoperable yes because if we want to have a chance to employ artificial intelligence data learning or I call just algorithms they're all driven by data and if you put rubbish in you get rubbish out so maybe James can tell us a little bit more about this linking data and creating knowledge graphs so a couple of speakers comments from the floor we're all researchers but we're all different types so I'm in different camp I think for most because I'm the citizen science DIY do it yourself so we have a completely different view and I sort of call this like the equivalent to the unbanked in Bitcoin so I think we will go for this over an identity sandboxing approach so this in this extreme form it just eliminates the data infrastructure problem because we don't share any data we keep it to ourselves but it puts all the onus on the computation as Dimitri said and that's still in bionic form but I think WebAssembly will come and give us that security in terms of even as a citizen science I do it with wearables the use case that Conrad mentioned and I've got various types of brands of devices but they're all heart rates right so I have to unify the heart rate data type and so tomorrow I think I'll take one of these ten minute slots and talk about a coded project pseudo coded talk through project called heart chain that guarantees cryptographically across the community a data type and a data type and then encrypted to the raw data coming off a device and the third thing I would mention is that there is a lot of money and data you only have to look at the ICO of Filecoin and those people do reach out and come to our events to be fair but I would say we're getting a very tokenized in contribution from them because I've got some heavy engineering to do my back to them is that if you may deliver a solution but if you do it in isolation from the science community it may or may not be the right fit for us and I guess I also have one more question probably for Dimitri and Conrad and I think it's also very important one and that's data ownership so it's very complicated so universities make claims on your research data you have certain rights to your data then there are like national legal there's national legal framework funders make some claims so like who owns it in the end and what are your thoughts on the problem well that's definitely a tough one I mean and you what is missing also the patient right if you have kind of a clinical study of the patient in there in the end it's his or her data and he or she might donate this but maybe to a certain restriction for that piece of research but maybe then another one another research that pops up that would like to reuse this that's a super tricky issue and it's also between different jurisdiction different countries this is super tricky and I even think we've once we have the technology solved this will be one of the biggest issue harmonizing this in the different countries I mean with a European Union you might have one chance to get this done in a right way but I think we are far far away from solving this unfortunately yes I have two comments one is regarding the blockchain solutions which are now designed for helping science we hear different stories and they sound like they are the ultimate solution what if we have a solution which is based on different blockchains or not blockchain based solutions but they are interoperable we did not hear so much so far about this that there are multiple ways to solve this problem what if they could intervene with each other we can choose one solution that's completely fine and we can retrieve data with the other method is there a possibility for that? I think that's probably the solution we should aim for as was mentioned before every research field has different needs and we don't need the same tools so we should have something that we can actually customize to our own needs but we have to make I think we should allow these different platforms are able to communicate so that they are interoperable so for example that chemistry researchers can communicate for example with medicine researchers right about drugs and patients data so that can all but we don't necessarily have to use the same platforms because obviously we'll have different requirements because chemistry research has different requirements compared to like patient privacy and clinical trials for example but it is connected and I think that's how we need to we need to make it flexible and interoperable and I think that's the that's the key and now whether it's based on blockchain or something else I think it's less relevant as long as it's possible to exchange the information yes I agree with that and the second comment is that we heard the technological part of it and we hear that we want we want scientists to go along and use these fancy tools why don't we take scientists into the development why don't they choose what they want to do with it that is a very good comment and as a researcher trying to build infrastructure that's what I came to realize because oftentimes you have funders who kind of hire someone to develop certain tools which are then completely useless because they are not really developed with researchers for researchers they're just here there you go use it and it doesn't really fit into the people's workflows that's why I said it needs to be flexible so people can customize it but it also needs to be easy to customize so you don't have to go and learn everything about the blockchain it should be possible to just do it in a very or even have dedicated people but then we go back to the problem of maintenance and support for the infrastructure which is just it hasn't been the case up until now so we have a unique opportunity to actually build something new and different and think about what it is that we actually want to try to copy the existing solutions and put them on blockchain which I think would be a very bad idea May I add to those points I think this was done in the previous time that the solutions were put out there and now the scientists just have to enter and play around and they didn't come so this is the issue so I think meanwhile also the funders see that there has to be a community driven approach to that so it's not that you just build infrastructure by yourself but always a community needs to be embedded in these decisions and regarding your first question it's well having just one single solution would be great but I doubt that this will work out we need to have kind of an agile approach because we don't know where we end up so we need to have different solutions and then kind of a selection of that and consolidation of stuff that worked out and that didn't and keeping the chance to communicate between these different solutions would be then essential for that and a solution for the best solutions and it's still kind of research where it's science right we don't know currently where we want to end up and it's an open question and this is why we have to play around in different sandboxes and I guess I have one more question for Dimitri regarding the ocean protocols which I think is really exciting and interesting idea but how do you plan to actually bring people or do you have any what are you doing to actually engage people into using it spread the word so well we have a lot of bounties and ambassadorships and all these things basically saying that if you contribute to the network you become stakeholder in the work you get equity early mover rewards and there is a lot of basically gamification around that as well also like doing all these things it's working, it's perfect we have we issued in the last two weeks we issued three bounties and they all got already within 48 hours they got fully accomplished and we issue our native token so I think for us it's like an initial experiment but very promising I want to mention about interoperability and other things it's very important you have to look at what's the trade-off in each situation do you want consistency, partition tolerance availability of resources then you have to choose different type of tools but I think the clue to all these things is a form of abstraction like you would see for example how the internet is built there you have like the OZ model you have like seven layers of abstraction such that it becomes a very flexible system where every configuration it's possible and you don't have to care about the underlying network just abstract it in such a way that all these components are seamlessly working you don't have to care about how your model works in order to send a packet over it in order to create a connection in order to send an application due to an HTTP request it's all different responsibilities and I think that's really how the decentralized stack is working out creating those levels of abstractions what we are missing is the end game of the user experience because that's where the bigger companies win that's where the Googles and the Facebooks are stellar they create the user experience that's less worse than what you see for example I use GIMP instead of Photoshop like honestly I'd rather work with Photoshop but yeah you get GIMP and there's a lot of these things that are in open source and from researchers that's UX and that's basically also where most of the bigger companies get their advertisements in between or what have you the user behavior steering function so if you find a solution for that maybe we also have a lost mile of open source towards the end user I think we are running out of time but yeah definitely we need to invest more in the user experience which is for some reason completely neglected in almost every research application thank you for your attention and if you want to talk with any of us just grab us in the coffee break oh 30 minute break cup of tea coffee lots of more conversations yep thank you bye 10 minutes to 5 we're back okay okay hello okay we continue I just want to announce that we already got a lot of stuff done but we have to like address like three more serious working talks and then I'm not saying that the pre-dinner talks won't be serious but there will be also even more serious okay so be very bored later on okay and now I'm like handing over to Dimitra and test okay you can hear me okay I think we had all a great morning till now let's say a great day and we heard a lot about blockchain for science and I think now it's a little bit it's time to see how we can use actually blockchain in a different way for life sciences it's quite similar but we have a very nice speaker Jim Naus who is called Syncrogenics and they create a large scale distributed ledger and without words I would like to give the words to Naus to introduce his company and what they are doing thank you yes thank you thanks Dimitra I've actually known Dimitra for quite some time and we actually talked together in Switzerland beginning of the year so it's been interesting to see the development around this space and it was interesting this is my first time to Berlin and just going through this conference I realized that there's a lot of maturity already so I actually tuned my presentation a little bit because I wasn't quite sure where we are but there was some really good conversations and hopefully we'll just add on to this as Dimitra mentioned I work for a company called Syncrogenics it's a private company in the life sciences industry and there's basically building very large scale open technologies very much with the idea of interoperability by design machine readable data by design and very much this idea that you can build large scale sophisticated software small APIs and that's really the core of what we're doing and it's very much in line with the work that I was doing prior to this this job that started at the beginning of this year I was the chief software architect at the center of open control and prevention in Atlanta and during my time there we developed what is now in the open domain as open CDC so it's very much along those lines Anywho so I'm not sure about Germany or Europe as much but certainly in the US when it comes to proper healthcare there's a question of do you have the means do you have enough wealth so there's many articles just news about this do the poor deserve healthcare and at times the data actually doesn't back it up because they can't afford the medicine they can't get the treatment on a timely basis even their information isn't really received on a timely basis there's lots of examples this is one that I found personally kind of egregious is from CNN just a couple of months ago this pharmaceutical company CEO decided that it was a moral requirement not just profiteering to price couch and you can go and look it up and increase the price for a bottle of medicine for urinary tract infection to about $2,500 for bottle so I don't know if that's a moral requirement but I think the way it is right now at least in the US they're able to get away with it and I think that's something that is very problematic of many other problems that are in the space such as it's largely opaque people don't really know where the prices come from the information flows slowly there's a lot of inefficiencies I think most of you guys know this here's the top 10 most expensive medicine in the US that's a lot of money for one bottle of medicine so before I go much further who in here is in the health or pharma space alright about 5 with 6 like you guys probably know what I'm talking about and I've talked to Dimitra quite a bit I know that there's some similarities and there are some differences between at least here in Germany and what we have in the US one key one is this in the US we don't have this idea of a universal ID so if I happen to have 7 different providers and they use 7 different systems I am at the very least 7 different people under systems there is no ID that ties me together I think in Germany at least that's not as much of a problem but in a second you'll see why that is a problem as we talk so anybody heard of you've all heard of Moore's Law yeah who's a technologist here by the way alright good maybe 30% of us that's excellent so Moore's Law is effectively now just getting faster and better every 18 months give or take who's heard of E-ROM's Law ooh that's good they usually have like none or maybe just one person so E-ROM is a literal opposite spelling of Moore and it's not my thing it actually exists and it's really indicative of the big problem in the industry in that over the last 5 or 6 decades as Moore's Law has led to more and more innovation more and more cost savings and doing things faster at a lower cost it's been the exact opposite as you can see with the blue line in pharma and life sciences where the return on R&D research and development has been declining and that is one of the reasons I alluded earlier about the price gouging that's one of the reasons why companies are going to feel well maybe it's okay to do so because they're becoming less and less efficient in actually going through the full life cycle of drug discovery and doing what they're supposed to do of being patient oriented alright so how does this stuff tie into blockchain and I do want to kind of be intentional those of you guys I know we have a good group of really well informed folks here and and of course the conference title is blockchain for science and as was my title blockchain for life sciences however I think it's important to understand that if you're specific about it, blockchain really is when we're talking about a sequential linking of blocks that's really kind of where the idea comes from there's a genesis block there's a history that's retained forever however the silver ledger technology is a bigger concept than that it's similar in the context that you have data that's distributed over many nodes however you don't necessarily have a genesis block you don't necessarily retain the entire history depending on which protocol you use and for what I do and the work that we're doing we are actually implementing DLT as opposed to blockchain per se and I'll get a little more specific but just a little bit about this section and the other thing is I'm a huge believer in the public DLT or public blockchain for many of the use cases that we're dealing with in healthcare public health, public causes, life sciences and there's many reasons for this I'll get into it in a second but I think largely in order for us to build the network effect we need to allow people to join in join in a permissionless way to think about long term governance because when you have a private network it's easy to get started but if you have global problems health problems that cross boundaries cross geospatial and geopolitical boundaries you really have to think through this because if you're a little governance group of three people the three leader nodes if that worked for ten nodes would that work for ten thousand nodes across different boundaries and different geographies and different time zones and things like this and I'm a big believer that at least from what sort of things I'm looking at public is the way to go honestly if I'm being overly facetious I think a private blockchain has no more than a sexier name for an extra net ultimately you have a leader node with a unilateral decision making ability and it's opaque so if you buy into public blockchain I think you really need to understand it's way more than just technology the technology is actually the least interesting thing about it to me what's really interesting is this idea that you have a gaming theory concept token economy I think you have to really explore that particularly if you think in large scale blockchain and public blockchain the other thing is this idea of how do you affect human behavior somebody mentioned this a little bit earlier I think it was in some of the earlier morning conversations you're asking people who have been comfortable putting all their data on facebook for 15 years or however long microsecond break has been doing this to now say hold on a second the data has actually been sitting on my phone and I'm going to have to maintain some kind of a private key and figure out shared secrets and things like this that's a human thing right so this idea of a decentralized culture is not easy and it gets into all kinds of things that are way more interesting I think than just technology alright moving on so I think I've largely mentioned in fact most of you guys have largely mentioned this already so I'm not going to belabor it in the world of DLT what I'm looking for as well as security and trust everything starts with trust if you don't need to infuse trust you don't really need a blockchain or DLT because why bother I mean if you're working with seven people and all seven of your friends it just isn't worth it but I think this idea of machine-based consensus is really really important you know and hence what I was referring to a public DLT I think and again there's many different consensus algorithms and you have to pick and choose the right ones if you're thinking about Bitcoin or Ethereum as an example they use proof of work right which is by design slow by design inefficient by design it delays things so there's a sinking period by design every note has a copy of all the changes before a transaction is validated but that's not every consensus algorithm and there's a matter of ones again smart contracts we'll talk about this last but not least I think it's really think through this native cryptocurrency and again a cryptocurrency is not yeah I think the name is kind of confusing and maybe low misleading it's not just about a liquid digital asset that you can trade I think you really think about it needs to think about it as some kind of a utility token for your network that has some kind of intrinsic value or unit that you can exchange anyways I think I've somewhat of folks talked about this at length so but be anybody heard this be grateful from yeah so go and look it up be grateful it's John Oliver from early in the year so yeah exactly so the thing with blockchain is it's tamper proof right but be careful because if you put garbage in now you have tamper proof garbage forever right if one of your blocks happens to have garbage in it or if you have a smart contract that's to cut bad code in it guess what I mean it's a pain in the butt to change that so there's a price to be paid for having this immutable or I think it's really tamper proof technology another thing is this so this lovely statue here our little cat that's a physical thing right it exists it's on this table because I want to put this on the blockchain that's analog blockchain is native digital and it's virgin territory it doesn't nothing exists on it so now you have to uniquely describe this or this class right so that is not a trivial challenge at all right in the world of health almost all the health is legacy health data it exists in existing electronic medical record systems electronic health record systems many other payment systems etc etc that's so-called off the chain how do you map it uniquely to the chain trust me it is not a trivial challenge and many people don't think about this very carefully I did mention this and I think this whole idea of scaling the governance is really really really important because I hope all of you guys want to do big things you know our focus here is science and collaboration and that's a really big thing I'm working with some folks around clinical trial collaboration and it is larger scientific but we want to scale it we want it to work across the globe so think about the governance even if you start with software how is it going to work as you go from your little community to your county to your country to your region to the world you know it's not trivial and also you have to make sure it's not and again just software or people it's a combination of the two because at some point you're going to have to deal with things now a good example is the forks that have happened with Ethereum and Bitcoin now if it turns out if you look at Ethereum Vitalik has been a lateral decision making he decided you know a few years ago that who lost all this money he decided to create a fork on Ethereum is that a good thing or is that bad I don't know it depends but if you have millions of users is that a bad thing? it's a really bad thing it kills governance it kills trust so we got to really think through that anyways be grateful there's a lot of use cases here that I think I've actually explored almost all of these we talk about the tracking the generic drug supply shortage problem in the US we have a real video an example of that we've built this out but there's many who can tell me what's missing anyone? what's the big one that's missing no not quite I'll tell you because you don't have that much time if you notice I don't have anything there about a master patient index right I have nothing there that's about at least in my world in the US and what I'm dealing with and the reason is this the trigger to anything that goes to the individual patient level is identity management large scale identity management that works across all the chains it's completely unrealistic for anyone chain to be their chain that's crazy I mean we love Hedera Hashgraph but by no means expect that's going to be their chain right? and a lot of Ethereum people like Cosmos was here earlier and we've got the Lightning Network all this other stuff bottom line I think the chain of chain thing is going to happen but are you going to have identity management across all of this stuff and if you don't the idea of doing patient master index or anything at the patient level is probably not realistic at least my opinion so what you see here is largely about aggregate data largely about anonymous data largely about maybe data that we're using that's already in public form because it's already been anonymized or redacted or something like this it's not at the individual patient level and that's a key I think key qualifier alright so I like this code it's not the mountains that way it's the pebbles and the issue in my world the pebbles and the issue are data most of us in the world of healthcare and life sciences are on the left side of this picture who's on the left side of this picture dealing with internal data sources okay who's on the right side dealing with real-time data streams okay gonna mug that guy he knows more than the rest of us so but the thing is the value is on the right side if you're looking at the left side your internal updated data sources or in our case largely public data sets you're basically hindsight you're forecasting based on what you already know but that data is often old in my world of public health at times it was years old sometimes it was many years old that's not really good right I mean what we're going right now we're real world evidence and that's a big thing I think you hear a lot of pharma companies and other folks talk about it whether it's patient generated data whether it's wearable data or whatever else clickstream social media you name it you want to be on the right hand side now if you go the closely go to the right hand side as this picture proves the more value you're going to get from it in this inside continuum right and it makes sense and if you do anybody I know I was talking to several folks and they're into machine learning and AI and you know the more data you have the faster it is right in most cases you can get greater insight right there's some exceptions so that's the idea and again in our world of trying to understand a patient so the patient I think to me has three pillars of data there's a clinical data which I think most of us are familiar with that's in the electronic medical records there's a genomic data and one of our speakers colleagues was speaking about that just before it might have been Conrad I may be mistaken and then there is your lifestyle data right so if you have the three now you have the holy trinity now you can really see the insight and I think that's one of the reasons why we're doing what we're doing you know my company is because we're really trying to build systems that allow us to get to the right hand side of this I think what you'll see and I think it's already happening Facebook and Amazon and Google have largely grabbed a lot of data but I think it's also quite likely that in this distributed computing world that that could happen particularly companies like IBM and Consensus as the quote-unquote leader and governance for this decentralized computing they could effectively create the same thing that would be a terrible thing right that would be like the worst of both worlds going to do difficult things with decentralized computing and yet giving control of the data to one or two entities can do that right certainly not for health I'm a big believer in this last bullet point that we really need to create open technology as pipelines as conduit so the data doesn't move in fact in the US if the data if my medical record data exists on a particular electronic health record system most likely that system the software has a license ownership of my data and I mean they do so the ability for me to move it is not really there but the ability to create conduits to it in an open way you can do that and that's kind of what we're seeing in this space again I'm not sure how big open APIs are here in Germany but I'm guessing you guys are probably quite advanced in this thinking and the US has actually been pretty late but there's all kinds of new movement around this place largely based on the 2016 what's called the 21st Century Cures Act and it's now law that every electronic medical record and electronic health record system must through an open API provide at least basic health data for any other system to use with consent I mean it's not willy-nilly obviously but with consent and that's a big thing and that's leading to all this stuff in fact you look at Apple which is not the company you know typically think of as being open they have lots of open APIs from the Apple Watch and the health kit they can use through fire to get to other things so this is a movement and this is really kind of our thinking and this is kind of what I think of as building open software I think of it largely as what a theme park would look like so if you go to Disney Euro you pay your I don't know 99 euros to get in for the day you get a wristband right that shows you know you pay it up and you know you're yay high and you can go on a fast track or whatever if you go from the racetrack to the lake to the roller coaster the experience is different it's not the same experience yet you haven't left the theme park right the souvenir shops are the same the security guards are the same the monorail is the same etc it's the same thing with software the fact that we can have an API gateway just like a turnstile you go and you get a session token that allows you to reverse different playgrounds such as right at the very top we have data set alarmization which is what we use here on the right we have DLT apologies I slow washed out for doing blockchain type things whatever but the important thing is these playgrounds are not coupled together you could have one construction firm building your DLT and a whole different one you know building your I don't know machine learning and they all work because they all follow the open API spec and they all use an API gateway that would be a low example everybody has been to amazon.com right the homepage how many APIs do you think go behind that page anyone know any ideas not quite it's about 200 or so at least last time I looked but that's a pretty that's a pretty crazy thing though right that one just the homepage has over 200 small pieces of software in it that's why we think this kind of idea works if you're interested you're more than welcome to read this blog that I wrote by this about a year ago when I was at CDC that's really what we did at CDC that's what we're doing for open pharma it's obviously more than just functionality we have a blueprint layer which is largely open source software and we also have really the secret soft of building software in this way is DevOps modern DevOps to do automated continuous integration automated continuous development automated monitoring at the microservice layer and so on right so I won't get into like a software one on one in this but this is roughly how you do it we like to make our APIs our application programming interfaces really singular and atomic so like one API that's just one thing like get something as opposed to get it the duped parts and things like this just do one thing and do a well make it small and make it very easy to deploy and then what it looks like as an actual application is something like this so this is a real application this is our data set and my session application this is exactly how we built it and then so as an example if I take my advanced reporting API or the risk scorecard API those are repurposed in several other applications and now by the way one of the things we're doing is we have a marketplace just like the Apple marketplace where any one of you guys can go in and use our APIs amongst your own you could use our data lake, you could use our search you could use our DLT, whatever you want to do but you don't have to be coupled to the rest of the theme park you just use the specific things that you need I think that's a very important concept in healthcare it's really largely understood in technology because that's how technology has been built for a long time well at least five years maybe ten years but in healthcare we are largely lumbered to this giant monolithic applications where you make one change a year to make it that change of production and that's just ridiculous that doesn't allow you to do world data right, you're stuck and I think that's a common story okay, so I mentioned open farm a little bit it's not by any means the only one of its kind just in the life sciences space there's open CDC which is again myself and my team built that and released the public domain and there's open FDA, there's other ones as well in many other industries there's many other ones AI and machine learning spaces a ton of open AI and machine learning libraries and frameworks I encourage you guys to look into it okay, so how does this tie into to distribute ledger technology and blockchain so this is what we've done again I know it's very hard to read the details so you don't have to worry about it but really the idea is this for tracking generic drug supply problems in the US there's a cast of characters that we have to identify the FDA as a regulator they are the user, right they are the ones who want to know what's going on but then there's active and inactive manufacturers there's distributors there's group purchasing organizations that purchase at large scale and then there's pharmacies I'm simplifying a little bit but that's largely what the space looks like this is the architecture we have again it's actually pretty simple it's actually based on using asynchronous message queuing using Kafka for this POC it's using the Amazon SQS simple queuing services but we're using Kafka for production but it's a pretty simple architecture this is not that difficult what's important though and somebody else mentioned this it was in a panel right before me I was getting ready paying enough attention to the Hedera Hashgraph it's what we're using that's not that interesting because nobody really cares what they care about is what does the user experience look like is it consumer grade and I would encourage you very very strongly you gotta think noise versus signal there's so much of a blockchain and DLT that's noise think of it as plumbing, as infrastructure I fully believe that in 5-10 years there will not be a single blockchain conference anywhere because there is not a single SMTP conference anywhere SMTP is protocol used for getting your email back in like the early 90s there were SMTP conferences but it's plumbing it's the pipes that connect things so I don't think honestly I think this thing is gonna be infrastructure what's really interesting is what you do with it so this is a video of our work, hopefully you can hear the audio hello and welcome to our proof of concept demonstration of OpenPharma's generic drug shortage application powered by Hedera Hashgraph in the current version of this use case we are oversimplifying the manufacturing issues in order to show our solution to make the generic drug shortage information publicly available quickly and accurately in real time our login page will provide proper authentication verification for allowing access to the authorized profile view as an administrator I am able to view and act as all user profiles this use case contains several user profiles such as the FDA regulators who can view all the incoming information in real time FDA inspectors who can instantly create and submit inspection reports on factories and manufacturers distributors pharmacies and group purchasing organizations who can easily perform actions such as reporting new facilities updating their current status as well as report generic drug shortages on the fly going back to the FDA regulator team view here you can see our recently reported drug shortage with Everest Group you will also notice that the live feed allows all new data coming from all users to append to this list and update our bar graphs for real time updates of the generic drug ecosystem the FDA regulator team is also able to filter out results and focus on specific user groups such as manufacturers where you can view factories and inspections as well as distributors pharmacies and GPOs where you can see all generic drugs in stock or in shortage through bar graph visualization per user group as well as specifically within each facility that concludes our POC demonstration of Open Pharma's generic drug shortage application powered by Hedera Hashgraph thank you for watching I think the most interesting thing about this is really that concept we had at the very beginning that we are trying to build near real time data systems that's really the giga and that's why we chose to use Hedera Hashgraph because it's a not to get too technical but it uses what's called the asynchronous Byzantine full tolerance consensus algorithm which is very, very fast and the technology essentially gets you to a validated state of a transaction within about two seconds at about 100,000 plus transactions per second so all to say if you want to track something in real time and you want to have some kind of a DLT backend in our opinion it's a pretty good option it's not the only one by any means but it's a good one now to be clear though this is not a blockchain there is no genesis block it uses what's called the directed acyclic graph consensus there's some pros and cons with that but nonetheless it meets our needs and again going back to my comment about infrastructure if this works if it provides you a trust cryptographic trust if this provides you the speed if this provides you transparency then does it really matter what protocol you use that's our thinking anyways just to wrap it up this is kind of the roadmap if you like this is the way we go about doing this as you can see this is largely about open source open technologies I didn't mention this and I'd be happy to offline it if you like but I'm also a very big believer that in order to make this public DLT work you have to use micro payments you have to have services that can be consumed with minimum amount of payment so you get customers immediately so it's not free and you don't have an advertising model we're not trying to create another Google but the per transaction fee is very very low because you expect to have a real time system with many transactions anyways that's all I have for you thank you thanks a lot now I would like to give to the next one I'm not really sure who is now the next I see here yeah okay great I'm Robert Peters and I'm with Orchid I'm the technology director for Orchid and I wanted to cover identifying identities Orchid identities in the blockchain and so what's fun about this conference there seems to be actually a pretty wide variety of people there's technologists there's admins here there's people who know what blockchain is there's people who have no clue what blockchain is and so this presentation will kind of cover a little bit of a lot of different subjects and just if you don't understand one thing just kind of bear with it acronyms we all hate them but they're better so what is Orchid the organization first of all Orchid is an acronym it's the open researcher contributor ID we're an open nonprofit organization and we're run by and for the research community we provide researchers with a unique identifier the Orchid ID that reliably and clearly connects them with their research contributions and affiliations and you'll see an example URL that's an Orchid identifier and there's our domain and then there's a 16-dentate numeric ID that kind of identifies who that researcher is and if you click that for humans humans resolve to a record that kind of looks like a CV it's not really a CV but we'll have a list of works or different name variations that you won't recognize in your research activities we have about 500 systems that have integrated Orchid ID and that's growing quickly and those general use cases would include grant applications manuscript submissions interest systems, repositories we've been talking with open pharma initiatives it's a pretty general identifier useful for any academics scholar or research space and so we use the term researchers a lot but actually we include admins and we include other types of scholastic work so I'm going to say researcher a lot but really it's a very inclusive term for us so the researcher typically how they interact with Orchid is an institution will ask them to authenticate their ID and once that institution authenticates the ID they can use it to collect information about the researcher and then attribute the researcher correctly in their metadata and in ideal situations that metadata gets pushed all the way to other systems that include publishers, employers and funders and eventually hopefully it gets into the Orchid record and we see that nowadays with things called crossref auto update where when somebody publishes their work they're notified by Orchid that it's been published before the publisher or anybody else notified them because some of those systems work quick enough other systems don't so but we want to get there where it works that way for everybody oh yeah the technology this is going to get exciting the Orchid tech stack we are a typical Java web app so this is like a term that was popular 10 years ago 20 years ago the good news is though we're open source we have a public API that's CC0 so any information the researcher chooses to share becomes CC0 and the researcher controls what information they share and then we have a member API and the member API allows our members to write to the API and then adds on a few other things like some information that the researcher may want to share with our membership and not the public and a few things that convenience like webhooks access to the record is controlled by the researcher so the researcher gives permission to our members to read the record or push the information in the record and that's via OAuth2 another fun protocol and finally no short term blockchain plans so why am I here yeah so I mean we're kind of earlier we heard talk earlier about we just do a lot of stuff in a centralized manner and it's great why don't we just get to it because nobody really cares blah blah blah and Orchid is one example of that working but we are actually really excited for blockchain and if you want to understand why you got to read our vision statement Orchid's vision is a world where all who participate in research, scholarship, innovation are uniquely identified and connected to their contributions and affiliations across time, disciplines and borders so our mission is not Orchid is the entirety of everything that's not what we want to do our mission is to make sure researchers are connected to their outputs and so often I talk to people in a lot of blockchain people to you they hey Rob come on I want to talk to you we're doing something and we think Orchid looks like this this is what they think Orchid looks like okay let's talk some more and the reality is Orchid is actually just part of research's identity so you have your university identity you have a government identity you have a LinkedIn your social identity actually ends up being pretty important when it comes to research Twitter, Orchid record every time I look or dissect the problem there's one more researcher identity need I need credentials to access this equipment or access this collection of books and so Orchid we don't see ourselves solving that problem alone it's a community effort and really we need the community to kind of address all the different types of identity just to name a few what we do is like how do you correctly credential some of these national identity or local university identity and the social identity needs there's a lot of problems there that Orchid's actually never going to directly approach so instead what we do is we offer a researcher identifier and a record that can help connect researchers to their many identities and activities and what that kind of looks like something like this we'd really like to see the Orchid identifier used to help attribute metadata and all these systems out there and then have that metadata point to Orchid record and ideally vice versa we want that metadata references in Orchid record that we can point back to the source of a lot of these things great so now we've kind of covered the identifier and that's really the core of what Orchid does but now let's talk a little bit about how that helps connect with other identifiers, mostly identifiers about research outputs you have research papers, university affiliations peer reviews, grants equipment, researchers do a lot of stuff, conferences right, we're at a conference people are producing at conferences, how do you correctly attribute that researcher to it and every time we look there's yet another thing that probably needs attribution so researchers are doing a lot of work out there and they're not getting attribution correctly and this graph kind of shows a little bit of where we have good coverage if we're talking about works researchers actually Orchid via crossref and other PID providers provides pretty good coverage you can push a lot of different types of works at Orchid to have them correctly attributed but when you get into equipment it becomes very the community is not there yet so we're trying to facilitate building out infrastructure for attributing grant awards, equipment, peer reviews researcher resources which is a new one that's coming up but there's always another thing we need to try to figure out how to connect and attribute researchers to and currently this is just a short term roadmap of new things that most researchers are familiar with PID such as a DOI so I did a DOI, my paper is now official and they feel good about it that's the extent they know they can click this link and it resolves through their paper but we're trying to help the community develop the same kind of infrastructure for affiliation types researcher resources and grant IDs and there's all kinds of other things out there that we also need to connect to and then I used the term PID and I was like oh wait a minute there's lots of people that probably don't know what a PID is and so I tried to think of the easiest explanation I could come up with and it's a it's a resolvable, actionable durable identifiers that can be used to locate and describe things and typically we see this as URLs that exist forever and from Orchid's viewpoint we really like URLs that resolve to metadata for both machines and humans so you see some that do one or the other and we really want to do both well and even beyond the activities that I've been referencing there's lots of other things that we need to help connect researchers to there's different profile systems right you have your NIH profile and you have your LinkedIn profile you might have a profile on Scopus and so depending upon what areas you are and what areas you move into you definitely have more than a few profiles how do we even connect a researcher to their Google search results I mean that kind of ends up being pretty important in the research community so many types in the name they pop up government identities somebody brought up Researcher Gate earlier today well how do we connect that kind of profile and all kinds of stuff that really we need to help facilitate connecting to and so when you look at the scope of the problem I just kind of I'm quickly described at a high level it's huge like how do we connect all these things to researchers and Orca's viewpoint is it's a community effort we can't go to alone so we really need community initiatives to help make this happen which brings us right back to blockchain and so here's there's a lot of interesting space there's a lot of innovation going on and lots of possibilities for managing researcher identity and attribution of activities and so why Orca Plus Blockchain well the value Orca sees in it is it's immutable and distributed and when we're talking about connecting researchers to activities or activities are everywhere so I'm very distributed so having distributed systems and kind of correctly attribute to those things makes a lot of sense to us and specifically we really like we're really liking the innovation we're seeing in the verified claims built on decentralized self sovereign identifiers and also like some of the initiatives we see around tracking researchers activities with decentralized systems and we really would like collaboration on PIDs and PID infrastructure and some of those could be addressed best with blockchain technologies and so let's get down to the brass tax what are we really asking number one is if you're trying to attribute activities to researchers or attribute a researcher itself use the Orca ID and that may or may not link directly to the Orca record you could use an Orca ID or an external system the important thing is there is this ID out there where we're trying to make it easy to disambiguate who a researcher is add PID or PID like resolution to researcher activities pushed to blockchain so a lot of blockchain technology is very hard for people to understand the t