One again. Looks like it. All right. Have I got the right screen on? Yes, I see it. You're good. Okay, brilliant. So a quick introduction. Some of you might be aware that I currently work for the Australian Research Data Commons. I joined this year. However, prior to this year, I worked for over a decade at UMNSW within Dementia Research Centre, the Centre for Healthy Brain Aging. So for today's talk, I'm actually wearing my UMNSW hat, not my ARDC hat, and very specifically, my Centre for Healthy Brain Aging or CHIBA hat. So yeah, try and keep that in your brains. Okay, so the Centre for Healthy Brain Aging established a research bank. It was called a research bank because it was a combination of a data bank and a biobank. And I'll be talking a little bit about that and about our research agreements, research agreements again, we're using that generic term rather than data sharing agreements because technically, the agreements also allow for the sharing of biospecimens. So a little bit about what we did do. So our research was to collect data and biospecimens from a very vulnerable population, people with dementia or at risk of developing dementia. So people like the lady on the screen who is my mother who has Alzheimer's disease. That's her, for some reason, wearing a floral headpiece that she would never normally wear and showing her obsession now with plastic fruit. I'm not quite sure what that's about. But they're the kind of people that we were collecting data on. The reason we collected that data was for our own research. So to examine things like risk factors for dementia. To use that data as part of research collaborations, such as joining International Consortia, harmonising our data with other international studies and performing mega analysis on those combined data sets. And then as I put there, any other appropriate purpose. So an example of that might be research that we had not envisaged at all. That's not normally part of our research. For example, we had computer engineers and data scientists who were working on machine learning algorithms to improve the efficiency of analysing MRI brain images. And they needed training data sets for those algorithms and realised that we had data that could be useful to them. I've put linked government records in italics under the type of data we collect. Obviously we don't collect that data. It is data that we access though and use for our own research. And I'll pop up a little bit later in my talk. Okay, so we were doing our own research. But as I said, we saw value in data sharing for the broader benefits for research and society, but as well for our own opportunities for research collaboration. So we have to consider how to share data in ways that was not going to impact our own interests and rights as the generators of the data in ways that was ethical and also in ways that was considerate to legal requirements. And considering as we learn over time, not being from legal backgrounds ourselves, what we're actually talking about was intellectual property. We had to revisit and review these things many times over the years as the ethics requirements and research expectations around data sharing involved. This involved iterative consultation with researchers with ethics committee and the UNSW legal office to establish requirements and solutions. So the first thing that we needed to identify was what our primary investigators requirements were. Obviously we had ethics and other governance frameworks to comply with. We had a requirement to review and approve use of our data. I put requirement involved there. Again, that's something that was going to pop up a little bit later as I talk. Our rights to acknowledgement for any use of our data and something that we built into our agreement, which was the right to request involvement in a project accessing our data. It's different from authorship and it's not mandating that we have to be involved but that we could request involvement in projects. So this was all discussed and decided on quite early on and was distilled into a document containing our governance guidelines. That became a foundational reference document for our data sharing practices and a reference document cited repeatedly in ethics approvals and renewals over the years. Guidelines were established a decade ago and remain relatively unchanged over time. The next step was to address ethics requirements. So that's the requirements around consent for data sharing and of course they have evolved. The text that I have on screen is actually the current wording in one of our current consent forms. I thought some people here might be interested to see a specific example. The key elements there which I've highlighted, the reference to future unplanned research, that the participants privacy and confidentiality will be maintained and that we will control access to data. I remember in the previous slide I highlighted that requirement to review access to data now. I would say that that was something that a decade ago we thought well yes that seems like a sensible thing to do but when I get to the end of this talk we'll see where that may be an issue moving into the future. A key thing I'd highlight is that this is really essentially principles-based. It doesn't refer to specific procedures like where the data will be stored or how the review or approval process will work. This is in the participant information statement and so HREC deemed that the principles were sufficient there. A side point that I'd note to which is specific for human research where participants are unable to provide consent themselves such as in dementia. Our HREC required that we have two versions of our consent form, a standard informed participant consent, where someone is composite medicine is able to provide consent to things like data sharing or what they call a person responsible consent form. So where someone is not composite medicine, where they have dementia for example and can't provide informed consent. I'll note for people who work in that area wondering how to navigate that there isn't actually a legal or HREC definition for what a person responsible is. It's not necessarily the power of a peton or a guardian. But it was deemed by UNSW HREC as appropriate at the time. My suspicion with my research had on is that that will probably evolve and become more clearly defined in the future. The other aspect of meeting our ethics requirements, so obviously getting that consent or where that is not possible in HREC means it's appropriate, a waiver of consent to share data and we definitely were able to achieve that in some circumstances. The other thing that HREC wanted to know were the clear details of how data may be shared. So not the principles based but the actual procedures. Here we were able to refer back to that study governance guideline document as I said it was a very foundational document. And for individual studies, we had those governance documents but this evolved over time into the research bank so the data by a bank didn't exist initially. It came over evolving needs or requirements from our HREC to establish something like that but it really leveraged the same, a lot of the same wording that was in the governance guidelines. Okay, so as it evolved, details of study ethics application were updated to match this. So ethics application we referenced both study governance guidelines and the research bank operation on procedures. The last of those kind of three broad categories of requirements to address were intellectual property. So when we proceeded to establish the research bank it became apparent to us researchers as I said we don't have that background that what we were dealing with was intellectual property and that we needed legal advice from the university. So UNSW Legal has extensive experience not necessarily in data bank so they had some of the differently drafting agreements for sharing or collaboration around intellectual property. So the things that we realised through that consultation with Legal that we had to address were not just who could use our data or our background IP but what everyone's rights were with respect to the project IP so the findings that came out of the research or new data sets that were generated by use of our data. For those who don't have a background IP is very common clause in contracts so we didn't need to reinvent any wheels we just worked with UNSW's lawyers to identify the university standard approach and make sure it was appropriately fitted to our use case. Another insight that we gained from going through this process was that we realised we had to identify when a formal contract around data sharing was actually needed so we definitely needed a formal binding contract when we were sharing data with researchers from other institutions. If we wanted to share data with researchers within UNSW but outside of our primary investigative groups and the people listed on ethics approval we didn't need a binding agreement we needed non binding MOU and I suspect a lot of researchers are familiar with that kind of thing where you specify your expectations etc. And a third type of agreement was a student deed poll. I have to admit this was a requirement that I became aware of really just before I left UNSW I'm not really an expert on this but the purpose for that was essentially that even UNSW students aren't the same legal entity as UNSW staff so agreements and contracts with them needed to be different. The underlying point here is that you have to consider who was the legal entity that was actually going to be using your data and that would determine what kind of contract you would need and whether it was a binding contract so legally enforceable or whether it was a non binding contract like a memorandum of understanding. So ultimately because even though we're researchers in a research centre within UNSW it's actually UNSW who's legal entity and they're the ones who have authority to review and authorize any decisions and actions around data sharing but that was ultimately for the most part dedicated to us researchers to figure out how to implement this once they've kind of set the high level context for us. So just to sum up those broad things that we had to address there are questions that we had to ask ourselves when someone was requesting access to our data. I note the use of the term on-provide there so as I said in that previous slide we had linked government data we weren't the legal owners of that data we were allowed to use it by the owners of that data so perhaps it was Medicare or Department of Human Services but we didn't have the right to provide it on to third parties. Okay so looking at the process that we used to review request to access data. Okay so we had four stages. First was that someone interested in using our data had to submit a research proposal and we developed a standard template for this that recorded things like the applicants details, their planned use of the data, their planned publications or other outputs and we asked them to note their ethics approval details. This would then be reviewed by the research bank and the study governance committee that was to ensure it met our ethical requirements so that requirement to control access to data and it also allowed us to meet that requirement of investigators to protect their interests and their rights to be involved in projects that use data that they generated. On completion of the review process that's when we'd head into the formal agreement stage so that might be the binding contract, the MOU or the D-POL that was using those contract templates that legal helped us draft and we also added in any special conditions of approval so if an external institution or researcher had a project that we had an interest in we could put us a special condition. Something like Professor X would like to be, would like the opportunity to be considered for involvement in this project so again it's saying we have an interest there but we are, I don't think demanding saying we have to be involved just can we have a discussion around this and I think in most cases the applicants were very happy to have that involvement from the primary investigators. The last step of course once you go through an application review and contract signing process is to release the data and we also had a requirement to monitor publications that we're using our data. Also if publication, sorry if data requests needed to be revised so they wanted to produce more publications and they originally stipulated or required more data or changed the scope of the project in some way then we needed to track that as a contract variation for people who haven't had exposure to that that probably sounds like a lot and it's like oh I've already signed a contract now I've got to go back and redo it. It's most times it's quite a small thing and can just be agreed via an email once there's an initial contract in place. So that was the process in terms of data sharing agreements these were then domain components so that final contract brings together things that I've been discussing up to now. So we had those standard researcher requirements and terms of use that are really stipulated there in the study governance guidelines so again foundation will document reuse repurposed in the in the data sharing agreement itself. We had the university's standard contract terms so that was the templates that they helped us draft and really in data sharing agreement terms that is the foundational document and things like the governance guidelines hang off of that and as I said in the last slide there was a research proposal so that formed an appendix to the data sharing agreement saying well this is what we agreed that you could do with the data and the final bit was those special conditions if there were any on the data. So the pros and cons of something like this so the pros were quite significant. Over my time at UNSW at Chiba which was about 11 years we had over 300 requests to access our data now we actually implemented the same process for our own staff and primary investigators we did for people as well that helped us streamline and manage access and use of data and track it but there were dozens if not well over a hundred requests from external researchers all of these 300 plus requests produced at least one publication of thesis and more often than not we've decided as co-authors so there's a very clear academic incentive to to open your data in that sense. After I left this year and since since the end of March there being 34 requests to access our data half of these were from outside the primary investigator group and almost all of those were from other universities and institutions. The other thing about having a data sharing agreement is that it very clearly defines the terms the process and what we found is that although there's a lot of academia works on goodwill having clearly defined terms acts as a good failsafe because it will be a small percentage of occasions where you're sharing data where generally not from any poor intent but just a misunderstanding about what the terms of sharing are having documents like this gives you something to refer back to. Sure, my presentation is that I'm almost done I'm not going over time so the costs of setting up something like this well it is the cost to set up something of this into maintain the processes and systems but then also to manage the ongoing requests and releasing the data. My centre had dedicated funding towards this that's how we were able to do that. Another con is unanticipated scenarios for data sharing so one example is more recently we had a private company commercial entity in the EU who wanted to use our data to identify new ways of assessing biomarkers for Alzheimer's disease so very worthwhile research. We weren't too sure about it though because we hadn't really been approached by a private company before we went to UNSWA Trek and they said well no you haven't explicitly said that you're going to share with commercial entities so you're not allowed to do it. I had a separate conversation in more recent months with a contact at NHMRC and this story came up and I won't name names but they were somewhat outraged that that was the interpretation by UNSWA Trek because they felt that it wasn't in line with NHMRC's data sharing aspirations however I think what that highlights is maybe a gap between principle-based policy around data sharing and then the requirement of each separate organisation to interpret those principles into their own policy. I highlighted already that we had a requirement which we promised to our participants that we would review who would access their data. Why I wanted to highlight that was how once the project ends and once the primary investigators are no longer available to manage requests to access data how are we going to do this in the long term? I don't have an answer for that it's something that only more recently has occurred to me so I just flagged that it's something that I think we're probably ahead of the curve in terms of data sharing data sharing agreements but this is something that we haven't really addressed yet and then the other con in this is something that's only become clear as we've been implementing this more formal rigorous contract process it's a time that it actually takes to go through that legal step of signing a contract to put some numbers to that this is the time frame so since those 34 applications that we've received since the end of March the review stage so when the primary investigators view the project and say yep we're happy with this on average it's been about a week the longer you see there's an upper range of 66 days to approve a project I can assure you that tends to be when the applicant has been slow to respond to a lot of questions or before they when they submitted the application they didn't take the time to understand ad art collections or availability or terms of use and so we have to go back and have those conversations after they've already submitted the application the thing that has kind of really blown out and we don't have much control over is that contract negotiation and signing stage and as you can see there that's that's up to close to three months however the median is one day so for internal researchers and students once once the committee approves data access and signing the contracts very quick but when you've got the contract template that has to go to an external university and their legal office then they have their standard set of terms around intellectual property and sharing of data and a negotiation process goes on that is let's say it's a little bit slow and then the other aspect in the timeframe there is the data access as you can see again it goes up to three months there's a very specific reason for that that's not the standard turnaround time as I said this is numbers reflecting what's happened since March and that was after I left so and there was other staff turn over so new people had to take over this they were loading the job and we also had the COVID disruption and yeah so I don't think that number is truly reflective of how long it takes actually to release data okay so that's pretty much it I would just like to express my thanks to Vivica, Susie and Ginny who after I left had to pick up all the pieces that I'd left for them to do so thank you very much that's Chiba's links and socials and thanks for the opportunity to present fantastic thanks Kristen that was brilliant so I think we'll go straight on to Fiona's presentation and then as I said if anyone has questions for Kristen if you could add them to the chat and we'll address them in the general discussion at the end so Fiona if you can share your slides okay well thank you very much for the opportunity to come and talk to you so this kind of grew out of some work I've been doing at UTS since I've been there since the beginning of this year and we started having and we knew this must be a problem which other institutions are facing and so started having having a chat with some other people about what they're doing in this space and is there a way which we can make it easier for our researchers to share data so coming at this from and I mean what I'm going to talk about is will be much more sort of high level and breezy than the the level of detail and rigor which Kristen's just talked about with their data sharing agreement so as an institution data gets shared a lot all the time researchers share data the university shares data so researchers may be collaborating formally on a project they may be sharing data informally with um with colleagues um researchers themselves um or their own future selves are also a significant um consumer of of data sometimes outside of the original context in which it was collected so as researchers move institutions that they want to have continued access to the data that they collected um and particularly in um long running projects that they want to be able to continue to use these high-value data sets as they move around institutions from the university's perspective there's all sorts of data that we send out administrative data for reporting and for describing our own activities where I think there's a significant gap where universities could be sharing data much more effectively is actually with our own researchers so one of the you know we've got these communities of fascinating people doing all sorts of interesting things and I think there's an opportunity for universities to benefit immensely from the the expertise that we have within our own walls I mean one of the examples um I've worked at the University of Melbourne and there's significant campus redevelopment going on there and you know we have people talking very excitedly about treating the campus as a living lab and what sort of opportunities did we have for data collection and for learning more about how space is used and how we can optimize space you know and we have a whole community of researchers who are who work in urban planning and particularly people who work on topics like urban greening who were really interested and would really keen to be involved in this sort of project apparently keeping trees alive in paved areas there's a problem which was of interest to some of the researchers that they were really keen to be able to stick a bunch of sensors in the ground as the construction work was underway and just finding the channels for them to be able to talk to the right people to pitch their project to get the sensors in the ground to have some agreement about who was going to have access and ownership of the data if that that project went ahead was a much more complicated process than I think it needed to be and then there's data which is kind of research data but it isn't so much the property of one particular researcher but is held in a Gland collection a library or an archive of the university and so how access to that is managed by getting both internal and external researchers access to that sort of data so there's I mean you know you all work in and love this space so I'm not telling you anything particularly new by saying that there's lots of data and lots of people would like to use it for lots of things so within the so what we wanted to do was to create a base template that would help to ease that that process for researchers of sharing data particularly addressing the need of a researcher leaving the institution that they and who would like to take a copy of their data for ongoing future use and researchers sharing data among themselves we had a few instruments about disposal already we had the materials transfer agreement but that was very much geared towards sharing of physical stuff it's when you send biospecimens to a research partner and the research office in particular didn't really deem that a suitable instrument for handling data sharing we also have a template agreement for sharing of student IP because students are slightly different from regular staff members in that they they own their IP and so if a student has done a project as part of a bigger research lab how do we make sure that the university has the right to archive and continue to use data which has come out of a student project so we did have those instruments in place which were were part of a what we what we looked at when actually creating the space agreement we also had a look at the Osgoal licenses which some people will remember and the template agreement which the Office of the National Data Commissioner has put out and it seemed so what we would wanted to create was something a bit like the Creative Commons license suite that we wanted something that would be quite simple and straightforward for researchers to understand and to be able to customize according to their needs something that could be made appropriate to their research project ideally some sort of a workflow or a wizard but you know starting small a flow chart and a form is where we're at at the moment it needed to be sensitive to the nature of research that there are things in you know conditions in something like the ONDC template for instance 10 is working on the assumption that data is being shared between agencies and that there is that there are comparable terms that both parties can rely on and I think research is there are a number of things that make a research project a bit different particularly the expectation that the outcomes will be communicated and shared when the folks from the BI team had a look at the template I prepared for research and there was a clause in there about acknowledging UTS as the source of the data one of their questions was but what if we don't want to be acknowledged which may be the case when you're if you're sharing administrative data for reporting purposes but when you're sharing research data it's unlikely that you would not want to be acknowledged as the originator of that data and also recognizing that research is open-ended that questions check open-ended that questions change and particularly thinking about a researcher living the institution that it's more difficult to defy tightly define a project for which the data may be used because you know they may not know yet what their next big project's going to be and so finally and this is what certainly to do with what Kristen was talking about getting things comparable across institutions is also difficult one of the things one of the conditions that I wanted to put in was that you know data should not have a lower security classification applied by the recipient than it had at UTS but that requires that you're able to translate in some way what you know what does something being usually a sensitive mean at the receiving institution so that's working out those equivalences I think is going to be one of the challenges so where we're at at the moment we've gone with a decision tree because we do want the template to be able to accommodate different scenarios so the decision tree asks the researcher questions like you know is there personal information in your data if yes go to privacy is commercial use of the data permitted if yes you know insert these clauses if no insert these clauses so we've got a plain English agreement which will describe the the the data that's being shared and the nature of the receiving pro project and then underneath that we have the formal legal terms and conditions to back up that template but I've really wanted to make sure that we had a plain English that plain English version up the front so that it was the intention of the agreement would be really clear at the moment with research and administrative purposes are being handled differently and it just it wasn't practical to have the what I wanted to see in the template for researchers and what the the the business side wanted to be able to put into their agreement wasn't going to mesh happily into a single template so at the moment those two agreements are separate documents where we're at at the moment we're very testing the agreement the first request has come in that we're trying trying out it's a request for access to data that's actually held in a in an archival collection of the university so working with the library on that and particularly agreeing what is acceptable conditions for the data to be held in and what we mean by you know treating the data securely has proven to be the area where we need to do a little bit more thinking I think about how the how the template comes together and what our expectations are at the moment as I said it's a it's a word document we would really like to be able to see this built out into a wizard or a tool that a researcher could click through and that would build a base agreement for them that they could then customize and so as we sort of look beyond our own walls and why it's so great to be able to talk to a community like this as I think that there's if we can think about building consensus among institutions about what are they to share an agreement looks like what are minimum requirements are their terms that we can understand we'll build a common understanding of I think that will that will assist the process greatly and as part of the institutional underpinnings project which the ARDC is supporting for next year I would really like to be able to do some today take that opportunity to work with other participating institutions towards doing some more work on common terms and agreement terms and conditions for a data sharing agreement which you know ultimately perhaps the dream is for a nationally accepted template agreement that researchers can feel confident to use themselves for sharing data that was all I wanted to to share with the group today fantastic thank you so much Fiona and I'm finally we'll be hearing from Steve about his perspective on the ONDC's data sharing agreement template so Steve if you'd like to share your screen so that I'll share me and then try and get rid of me I will share screen you know I say I have three screens here in front of me so I will hopefully get the right one at this point and see how we go okay it's that one for now let's see how this works switch the screens here okay there we go so um I think we've just an administrative matter Angela is having all sorts of fun with waiting rooms so you might see a message about waiting rooms popping up periodically because I'm one of the go hosts I say we'll manage that as best we can but in the meantime I will be talking a bit to the a really nice segue from both Kristen and Fiona have presented Fiona finished up her points on saying could we have a template national data sharing agreement I'm going to talk about one of those templates um which is coming from the Office of National Data Commissioner we've talked extensively in the in this working group in this community practice area about what's coming with the the data of the DAT Bill from the Office of National Data Commissioner so there's a really nice segue there actually between the two I'm my aim here today is not to either champion or dismiss what the the ONDC has done it's just to really walk through what's in there and then you know picking up on what my colleagues have already talked about is to say okay well you know is there something that might be relevant is this the right sort of framing knowing that that also that we have a certainly the federal level of legislative framework coming which is likely to incorporate some of these discussions and I say I really like Fiona's last point about you know thinking about what I you know sort of some sort of collaborative arrangement of cross institutions and here I would define both government and academic and other research institutions and etc etc you know you know non-government organizations and others as well might think about that might be overly ambitious but as saying I think we you know there's a lot of common interest here and as Kristen's timeline slides point out there's potentially a lot of waste not wasting but a lot of time involved potentially time wasting that might be involved around this if we you know we're putting our heads together and trying to do something collaborative here might well be of use so I'm going to walk through just what's in there and just some commentary you know and I don't claim any you know personal ownership on this I have basically picked up what's in the the data sharing template and just you know highlighted the content that's there and just some commentary on the way through mostly just to highlight you know that these are the things that the being thought about from the the OEDC and and others and might be you know consultation with government agencies as an academic researcher and working for academic data sharing organization and collaboration with government you know what are my reflections upon that so just for those who haven't been in the space here I've just picked up what are the OEDC trying to do promote greater use of public sector data drive innovation from use of public sector data and build trust with the community around government's use of data so it's a very much oriented around support for you know access to government data and use of government data but as heavy users of that government data as one part of the the research environment you know the academic community has a strong interest here as well and there was you know that we want to be conscious of and certainly interact with on a regular basis so I say this is you know this document's been out since March of this year the there's the link at the top of the page here and I say I'm just reproducing you know literally content out of either the website or out of the actually the structure of the document itself and some brief commentary what's it trying to do this template well I say picking up from where Fiona got to it's fundamentally trying to highlight where there might be some template content that we can start working towards so this is not filling in the gaps as to what your institution would say but or what are the sorts of questions you would ask so it's really from the point of your data provider I think as much as anything and one of the things as a data user or as in fact I'm an intermediary for the most part Australian data archive works with agencies and researchers to connect the dots between the two how do we get you know data you know data sharing occurring between between agencies and users in an effective way so you know this is a you know likely to be I negotiate you know on a fairly regular basis you know sharing agreements with government to facilitate access for for researchers writ large so I'm not talking on a project by project basis what I'm trying to do is sort of set up a framework whereby we might enable you know not unspecified use but a framework whereby we can leverage ADA's existing data access protocols and procedures to enable access to data with the relevant participation of different parties in the process so this template really is a safe for me is I'm likely be a user of this template in my discussions with government going forward so what are what's the template trying to do implement the best practice guidelines work help government agencies produce agreements to share data effectively and say it's been working in some on station stakeholders and it's designed to be legislation agnostic so this was developed prior to the death pill you know going in practice and it's not intended as an implementation of the death pill that you know whatever passes because that there might still be some time away it's likely go to all the parliament soon but it is still you know there's still some work to be done there and the specifics will be you know will be laid out um but you know it's really framing up what are the sections of the discussion as much as anything so you can kind of see that the work that's already gone on now and is the in there um say and probably anticipating but not dependent upon what passes through the bill that might go through the parliament so you know so what am I trying to do as I said you know this is a late person view I'm you know my caveats at the bottom now I'm not a lawyer I'm not speaking on behalf of any of the the parties involved here it's really based on my own experience working here at ADA but I say it's not a new position that's not an official ADA position um and certainly it's not now in DC's position I'm not you know I have no role directly with the government in this way I'm a regular contributor to some of the confrontation processes that are involved I'm really just trying to think here about what are some of the possible implications here for the institutions and researchers um as potential parties do this agreement this or a temp agreement that might be built from this template and really thinking yeah I think reflecting upon what Kristen and Fiona have just talked about you know this is you know what would you do as a group I'd like to think about what we do is if we were developing an agreement where we were the recipient of data the user of data and having to negotiate it you know part of this discussion so one of the things to think about here is well how will we populate the content that's going to go through here okay so I say from here it's really I'm just the most part really I'm the content of the bill at the template agreement itself and just want to reflect on something as I go through so the basic elements of the draft agreement template of this it outlines the parties the purpose the duration the data sharing principles so now read here the five safes but as I say is the only DC have taken that further their interpretation of you know what was found in the five states but is their data sharing principles and aligning that with their best best practices guidelines that were published around about the same time so I say those principles will be embedded in the legislation and are similar principles are certainly embedded in the as I understand the South Australian legislation as well so you know we can try to see these as kind of a framing there are limitations to them and certainly in discussions even yesterday I was involved in a workshop with IAASIS and others where you know recognising limitations for example for Indigenous Day they're all for working across institutions but there are foundation modes that we can start with and then there's other things other conditions and arrangements and supplementary information but for the most part the core of the the template is really reflecting upon the data sharing principles and the and frankly I think on the purpose I want to touch upon what's there and how we might think about using that going forward so if we start with the part is the agreement the actual the template agreement actually specifies organisations not individuals so it's safe and you know not every data sharing agreement is actually an agreement between organisations but certainly the elements here are orienting around organisations rather than individuals so and specifying particular roles either as custodian intermediary or or as user so as I say I'm for many of us we might be custodians but you know here where this would like to be used would be as an intermediary or as a user um for those thinking about the datum as well I think that you know we can expect in the language it's including the document there is it's equivalent to an accredited data service provider is what an intermediary represents you know so someone who's providing you the data sharing or data linkage services right now that's an accredited integration authority um and we have colleagues from some of those organisations on the on the meeting today um but as I say it's likely to be you know read here accredited data service provider um is how you might think about that going forward it it may you know it doesn't necessarily require that um but you know if this was formalized okay we can kind of read that into that situation so I guess that's the starting things I would think about here is all I say what about unnamed parties is it the capacity the capacity to be looking at an agreement you know but for ADA's point of view we facilitate support um access for a large number of users across many organisations how do we incorporate those unnamed parties here that may not be directly relevant though it what we would think about instead is some of the on sharing of data and the dissemination protesters that you might think about that um you know so those unnamed parties individuals and other organisations might be you know might be relevant here um uh in the current template individuals in in named organisations uh can actually be specified in section 4.8 of the agreement so there is capacity to incorporate individuals into this um the interesting question I think is you know I put there is can or must you know if you can't have you know unspecified entities in there you know that's if you're negotiating one of these agreements that might be one of the questions is can you extend how do you extend the question kind of touched upon that in reviewing you know data sharing agreements as well um the broad um statement in item two then is really about purpose so the the items you see in there purpose of the data sharing project um you know so what's the overarching type or types of purpose I would kind of phrase it really consistent with where the I think the DAT Bill legislation is getting as well as it for you know research and development is it for you know what's the public benefit you know outcome of the you're kind of targeting you know uh and what's the specifics of the project and can incorporate sub-chode projects and you're asking include you know specific details there and then how the data shared will assist in achieving that purpose so it's not you know so it's the broad purpose and then specific projects that will be undertaken um so one of the questions in framing up some of these these agreements might be how comprehensive will the purpose need to be and what if new purposes emerge how do you you know it you know is there a mechanism for adding purposes um that you might be thinking of here or adding projects we're actually having some of these discussions and a challenge in in this in working with one of our partner organizations um you know finding this quite difficult how do you think about what might be a research program of an institution or a a research center how do you expand upon that that that becomes practically speaking rather challenging uh and how do you model that and that's probably for our template discussion example that's one of the things that we at ADA are thinking about quite hard because we're finding it difficult to think about that interaction of equal and projects into a broader research program um and that's one of the spots where the five safe starts to fall down is you don't actually have you have a safe project but not a broader program in which those program projects operate um item three talks about duration um some of the duration of the agreement itself um yep it's kind of picking up here but where this goes to next which is you know what's the end date yeah i mean this is specifying the agreement an interval through review will it be a one-off or periodic sharing of data so when you have time series or you know real-time data you know you're going to be particularly with administrative data you can see now this you know a regular fee becomes important um you know sort of is this is you know it's this one-off or or or so some sort of periodic arrangement what that might be can it be rolled over the the terminology that they're suggesting you know implications yes sort of involving agreements are are relevant here um in my experience um the that's one of the one of the challenges as well which is um having a finite end date or at least a review period um means you can say okay well you know when do we finish access you know uh and that sort of evolution um all that you know the end of the project becomes you know difficult new new questions emerge or ties into that sort of you know project and program development how do you renegotiate those is something you say I like the terminology thinking around review because it does imply that you might revisit that um but say the sort of that the finite end tends to be in my experience you know positively received it's like okay we we've got until that point and in time to the point of view of the data provider uh and then we might negotiate a new agreement how do you build in those sorts of review processes effectively is something that um you know somewhat to somewhat of a challenge um the item and item four is really where the heart of the agreement you know the template actually comes from and it lays out the the the data's area principles that you know you know what we would turn the five states you know in the broader framework projects people settings outputs data you know is really the elements there so here's you know um starting to you know fundamentally each of these sections kind of ask you to lay out some of the specifics of how this will operate in in practice uh where and I think the broad comment I would make here is this workplace sharing a specific set of content um but how you embed this into a broader program or a broader collection of data is where this starts becoming challenging and where you know um uh we might hit some difficulty in using this sort of framing um uh so you know the basic you know project statements you know what's your consent procedures you know what were the you know are you going to require approval processes so here's where the interaction between the institution and the data provider it's sorry the institution has used the data provider as provider and potentially intermediaries as having to confirm these things becomes you know a lot more involved you know christian sort of talked about some of the time frames that involved there and this is you know I have two staff you know fundamentally who you know this is what they spend their time on is reviewing and ensuring that there's enough information to at least make able to make the decision on these things not actually making the decision themselves but passing that information through um so where is the you know the public interest what are the procedures that you're using here what are the circumstances under which you can share data so we have agreements whereby we are approved by the data provider to um approve access for certain types of users or certain types of programs but not others um and what are you know what are the circumstances where you got to return to the provider you know so negotiating these these processes for a specific data set in a specific project is relatively streamlined but for a broader program and it can be challenging uh can you really and how do you release outputs and this is the one that's often you know the IP sort of questions and the the academic freedom questions and the moral rights questions this is you know what are you going to put into that how do you negotiate that with the agency that you're dealing with or if this is a template for use in other spaces and i'm not suggesting that it is right now but it you know again how do you you know who gets credit for what how do you you know review and and and confirm the appropriate use of something um you know that that starts in you know a kick in there um there's a state non-intermediaries so as I said the credited data share service providers is you know um kind of starting to be embedded within this template as well you can kind of read these in and you might be thinking about that going forward you know what's the set of infrastructures that are going to develop in here so as as intermediaries um you may want to be thinking about what your what you need to get incorporated in here to meet your obligations both to users and to uh data providers or custodians um you know so what are the data services that are going to be provided um what are the you know conditions that under which the data sharing can be done and what will happen to data at the end of the project um you know so end of life sort of questions here um we have different agreements whereby there isn't you know an end date on some agreements there is on others you know do you include review process again Kristen kind of touched upon this what happens on the appropriate use after that the first project is finished particularly if you're you know from ADA is one of you we largely deliver you know data delivery you know through through a web download so monitoring after the facts you know do you do that what sort of you know checking do you provide um there's a section on people uh so you know certainly you can specify personnel in here um are there any additional requirements that need to be met you know example this might be you know the ABS has their um data lab training uh what you know uh uh the Erica team um at UNSW uh have you know researcher training do you have training needs do you have ethics requirements you know internal review and from an organizational point of view that that second statement details of persons who are responsible for ensuring the requirements are satisfied do you have your internal procedures set up effectively at your institution to ensure that you have your oversight on these processes if it is required um you know so how do those processes flow down through your institution because it's the organization the institution university in my case that is like the signatory to this agreement not the individual so how you know what are your your obligations then and what relevant you know with the data custodian or intermediate provide support as well um so again this is the intermediate maybe think about the their obligations here so there's a lot of uh settings um how will the data should be shared where will it be stored and accessed um are you using a secure lab are you you know where are you storing the data itself um excuse me i'm just gonna some water these sorts of implications physical environments technical safeguards etc um data security data um you know what data then on the data itself what's the data it's going to be shared will any treatments be applied you know there's quite a lot of detail you could incorporate here do you have answers to these questions as you go through is there was a provider or as a user um because if you don't then this is where a lot of the negotiations that Kristen and Fiona talked about this is where the time frames you know pick up it's we don't have standard answers here or we don't have agreed answers here and populate that information can take a lot you know take a lot of time in my experience in working with agencies um i tend to start but the the the legal you know sharing you know discussion in the the processing and data um uh data management discussion about the same time it's very rare that we don't have the data ready you know ready well ahead of the actual um uh final agreement being that you know they're being finalized i mean it's the it's this sort of detail it that um uh takes much more you know can be done in parallel but often takes more time than the actual you know the data management side that that's going on uh and then you know from the point of view of the institutions and also from the point of view of the data providers remember what's the concern of the data providers is will you want you know what's going to be said about this at the end of the process you know what overview do we have all the outputs that are coming through from the point of view of the agent the researcher and the and the institution what are we expecting to get at the end of it here and how do you negotiate those things um so the IP discussions that people were talking about um you know i think starting to think about you know what what are our expectations here and codifying some of those is going to be much more important because we have standard language that doesn't always meet the the needs of the other party what are the the mutual obligations we might have that we could possibly normalize i don't know if that's possible or not but something to think about um the last parts that are there what are you going to bet data breaches who will be responsible for them and other you know other information that goes in there and approves you can honestly this is you know every one of these things this is 13 pages without any content my sense of this is you could be well we're looking at a document but you know even before you've actually got something that's finalized just drafting this is you know significant amounts of content potentially and every one of those items that that that appears on the page here um but there's also the case then i think Fiona really reflected upon this that a lot of these could well be populated you know to at least some degree in advance you know we know our answers here but we possibly haven't documented sorry possibly haven't written them down in the way that we might expect in the past so can we start thinking about ways of actually populating something like this agreement or similar agreements that Fiona talked about whereby we know a lot of the answers this and then we tailor into the specifics because this is just a template for the questions of being asked what templates that we got on the answers is you know a whole nother discussion there's a you know this is why we get the sort of time frames that Christian is talking about here um so some future considerations and questions for the group here has anyone had experience you know this has been around about nine months now what was your experience i haven't had to negotiate using this template directly but certainly some of the flavors of what i've seen are reflective of the five states the data sharing principles you know in general um uh how might we develop that sort of template response content you know examples being busy physical IT environment you know ISO 270001 is a you know you often in the accreditation procedures you've got content that would probably populate this core trust seal content we we got through accreditation and some of that's relevant i would think and then how might these template options interact with the forthcoming that pill ADSB is accredited users i think you know there's also the content here that the sharing of approved agreements is um there is language in the bill which proposes sharing of approved agreements so i mean you know how to help members feel about you know that that approved that agreement or at least some information about that agreement might be shared in this process i know my personal position is actually that's a good thing that it makes transparent the the and build should help to build trust in the use of a system like this but there are implications that are up you know ip and commercial imperatives that might be mitigating against that as well and we you know how do we how do we engage with those so i'll leave it at that um put those on the tables you know in a few times there's just some contact details there but saying i might just leave the those questions up on the screen um for folks to consider and we sort of we're hoping now sort of engage in the discussion as to you know what sort of divisions are coming up for the the community in this


The theme for the market make ETH Global Hackathon is the future of finance and when I was studying to become an actuarial fellow in financial applications there was this problem that really annoyed me, the diversification illusion. So we assembled the team and created a decentralised application called EtherTree that securitises laps risk and addresses the diversification illusion. Now a large part of finance is about managing risk and return and generally in order to get more return one must take on more risk. So if we have a blue asset with low risk and a low return and an orange asset with a high risk and a high return and we look to capital asset pricing models we see that a combination of assets isn't given by this linear relationship. No, a combination of assets can give the same return for a lower risk. Now this reduction in risk depends on the correlation strength.  Now when the market is stable we see that different asset classes have low correlations with each other and this gives us the belief that we have reduced our total risk but correlation isn't constant. We can use Archimedean copulas to model its fluctuations and we see that when the markets crash the correlation between these assets increases, thus total risk increases and our portfolio is undefended when it is most vulnerable.  Now if you want to know more about capital asset pricing models and Archimedean copulas I do have a few other videos on my YouTube channel that goes into the mathematics of it but essentially this is our problem, the diversification illusion. Now let's talk about the solution. The blockchain allows for new asset classes to be created as it facilitates securitization and we have the technology in the form of Ethereum. Now all we need is a risk that is negatively correlated with traditional assets so we want something that will go up when the market goes down and we found it, lapse risk. Lapse is when someone breaks their promise to make a series of payments or when they surrender their financial obligation. So we have the technology and we have the negatively correlated risk. All we have to do now is combine the two to create a new asset class. Now we know that capital asset pricing models, correlation, copulas are not the easiest of things to understand and so we decided to gamify our new asset class so that it has a better user experience. And our game is called Ether Tree. Now there are two types of players, planters and waterers. The planters, they determine the parameters and the risk characteristics of the lapse security. In terms of the game, they're planting the seed for the Ether Tree. The waterers on the other hand, they browse the various securities and pick one that they believe is fair so in terms of the game, they're choosing which seeds to water. Now the game has got four parts. Part one is planting the seed and this is where the planter gets to determine the parameters. The parameters are duration, payment frequency, payment amount, number of waters, start date, planters fee, bounty and lapse limit. We'll explain what planters fee, bounty and lapse limit mean in just a minute but essentially what will happen in part two when it comes to germinating the seed, the waterers will choose a seed to water and we're going to see that they're going to prefer a high bounty, a low planter fee and a high lapse limit and the rest of the parameters will depend on their own personal preferences. In part three, this is when it comes to watering the tree. Now the waterers need to make a series of payments to the Ether Tree contract. If a waterer misses just one payment though, then it's game over for that waterer. However the rest do get to continue and they get to reach part four which is harvesting the fruit. Now the planter gets either the total fund and this is if all the waterers lapse during the duration or they get their bounty back plus their fee and this is if the lapse limit is breached or they just get their fee if the lapse limit isn't breached. The waterers, they get either nothing if they lapsed, a share of the bounty plus a share of the total funds after fees if the lapse limit isn't breached or they get a share of the total funds after fees if the lapse limit is breached. So let's maybe talk a little bit more about this lapse limit bounty and planter's fees. So let's start off with the bounty. The planter deposits a significant sum of Ether at the start of the contract and this is kind of to lure the waterers in. If the lapse limit is breached, the bounty returns to the planters. If the lapse limit isn't breached, the bounty is shared amongst the waterers. So the higher the bounty, the more desirable it is for the waterers but the more that the planter could potentially lose. When it comes to the lapse limit, I guess the best way to explain this is through an example. So let's say the planter sets the lapse limit to be 10% then if more than 10% of waterers lapse then the limit is breached and the bounty returns to the planter. If less than 10% of the waterers lapse then the limit isn't breached and the bounty is shared amongst the waterers who didn't lapse. When planters fee, this is the percentage of the total fund that the planter receives at the end of the contract, although they have to give it up front and because it's the blockchain, we have transparency. An idea here is that if the planter sets it too high, you will scare the waterers away. This maybe go through an example to aid our understanding. So in part one, planting the seed, this is where our planter determines the parameters and this is probably the most important part of the game for them. So let's say they set the duration to be one week and the payment frequency to be daily and the payment amount to be one each and the number of waters required to be 100. Let's say the start date is the 15th of December and the planter's fee is 5% and the bounty that they're putting up front is 10 each and the lapse limit is 10%. So let's say they set this up, then let's see what is the best, worst and normal case scenario for the planter. So the best case scenario for the planter would be if all waterers make all payments except for the last one. Why? Because this means the total funds go to the planter. This means they get their bounty of 10 back plus all 100 of them making 6 payments of one ether each means you're going to get 610 ether plus any return from a liquidity pool but we'll talk about that in another video. So essentially you're putting in 10 and you got out 610 over a duration of just one week which is pretty good but that's the best case scenario. A normal case scenario would be something where 10 waterers lapse let's say right at the start and 90 waters don't lapse thus the lapse limit isn't breached. This means that the fee times the total fund is going to be the 90 payments times 7 because all the payments are made times the fee of 5% and we're going to get 31.5 ether plus any return from a liquidity pool. Here you're putting in 10 and you're getting 31.5 out still not bad but what about the worst case scenario? Okay worst case scenario is let's say 99 waters lapse right at the start but you have that one waterer that doesn't lapse this means you're just going to get 5% of 7 ether plus your bounty back so you put in 10 and you got 10.35 out and with gas prices that's probably not a very good investment but like I said this is based on the parameters that we are using in this example and this is what makes the game really fun and I guess complicated is that different sets of parameters are going to give completely different return distributions but let's look at the waterer with the same example worst case scenario is that you make every single payment except for the last one and that means you put in 6 but you get nothing out the best case scenario is when you make all the payments and everyone makes all the payments but the last one because this means the total fund is now 601 ether and when the planter takes their 5% fee what we see is that you put in 7 ether and you got out 570 now that is the best case scenario probably not going to happen so let's look at a more normal case scenario and this could be something where 90 waters make all the payments and 10 waters lapse off the payment number 4 so now our total fund will be 90 times 7 plus 10 times 4 plus the 10 bounty and we get 680 now once again the planter takes their fee and we divide it by the remaining waters which is 90 and we see that we put in 7 and we got 7.18 out now what we can see is that probably the parameters here were way too much in the planter's favor although having said that this is still a 2.6% return after a week and if you had to annualize this it gets you like 275% for the year but again these things depend very much on the parameters and what actually happens and what makes this game difficult to determine what your returns are actually going to be is because how many lapses and when they occur are unknown at the start now for the water is this is a simple game you pick a tree to water you don't forget to water it and you get a share of the fruits low risk low return but you're still getting exposure to laps risk and it's kind of interesting because the more people that lapse the bigger your share of the total fruit although the total fruit will be a bit smaller so it's not going to be a linear relationship between the amount of people that are lapsing and the amount that you're getting back now for the planters it's a little bit more of a complicated game because you need to optimize the parameters for the tree if you're too greedy no one is going to play if you're too generous you might make quite a big loss so it is high risk high return but once again you do have exposure to lapse lip lapse risk and generally the more lapses the more return however you still need some payments to be made so there's no point in making a bunch of fake water accounts that immediately lapse because then there's going to be nothing in the total fund so overall what we can see is that the expected return on lapse risk is unknown but and this is important lapse risk has a negative correlation to traditional assets think about it when markets crash there's a liquidity squeeze people tend to need cash so they tend to lapse on their financial products thus introducing exposure to lapse risk gives your portfolio a real diversification benefit making it more robust and lowering your total risk okay think of it like this with regards to the capital asset pricing model introducing lapse risk makes gives you the purple curve instead of the brown curve so we are lowering total risk in a portfolio of assets now look in this video we're just giving an introduction to ether tree another video will go through some of the code as well as some of the non-fungible tokens that you can also earn by playing the game now there's still a lot more for the defy community to do in order to revolutionize finance but we believe that ether tree by using the blockchain to securitize negatively correlated risks to achieve real diversification in portfolio construction is a step in the right direction thanks so much for watching and job make sure to to find out more about the project going to the following social handles


I'm the proud father of 13-year-old twin sons, Luke and Jack, and an 11-year-old daughter, Lila. And all three of my children play youth basketball. All three of my children have told me that they have the goal of playing college basketball. They've told me this on numerous occasions, and I told them that it was my opinion that each of them liked the game of basketball, but they didn't really love the game of basketball. Each of them enjoys playing, they like going to their practices and playing with friends and shooting around in the backyard, but they don't love the game to the point that it requires the almost obsession and commitment to what it takes to play college basketball.


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Well, three days after his team found the state semi-finals, Pierce football head coach Leo Polkamp has hung up his whistle. Polkamp retires with a 276 and 84 record and three state championships. Polkamp tells Lakeland News it was tough walking away after 33 years as head coach, but he felt it was the right time to give it up.


What's good YouTube? This is what you were back at y'all again with another speed art video back at y'all again With some more heat man. If you new to the channel, go ahead hit post Notification for me man. Go ahead and subscribe to the China cuz I will be posting Nothing but the gas meaning the fuel to the flame that fired at So make sure you stay To make sure you go ahead and become a part of this family, man You know I'm saying the heat gonna always stay coming Anyway, let's get right into it. You know I'm saying it's just a speed art grime video I had to do it my boy Travis Scott. You know I'm saying he really wanted the Most influential people today in our time. That's making great music. So man big shout out to Travis Scott. I Know I've been missing for quite some time man.  It's some no attention Because all I hate or want is your attention as soon as you give it to him That's when they take it to that next level. They gonna keep going with it. Oh, yeah, you looking now I got you off task. No Yeah, yeah, that's all haters want man is your attention Even when you ain't thinking of them So the best way to beat negative people Don't respond to him. I got to learn the hard way because I got so much pride that I try to But I have great people in my corner that tell me I gotta move More professional. I got a lot going.   Don't show it. Don't give no negative energy. No type of attention.


Good, what's going on everyone Sam here with late in sports cards We are ripping one box of 22 panini luminance football for Chris F. So good luck here at Chris. Let's do it dude I know clearly By the way, I'll take a look after this break Joshua because I know Kyle sent me something too, so Come on baby. Let's see something big. Have a good one Tommy. Thanks for stopping in congrats again, buddy Jefferson, Tyron Williams, Zemir White Rookie, Tyrick Woolen, Arnold Ebukite to 149 for the Talcans That's gonna be nice. Joe Burrow on the bright Jersey cart not numbered there And That is fusion of Camakers on the insert Just the Billy Rifkin Yeah, Joey B8, but I ain't terrible auto there at all for sure just a bill Tom Brady John Dodson Romeo Dobbs Jalen waddle on the sheesh to a hundred Jay sheesh waddle that is pierce strong junior to 249 We've got Leo Chanel Auto 220 out of 349 for the chiefs. He's actually like a rotational starter for the chiefs not too bad And dynamic rookie Stadium club I know for Vaughn dude is wanted nothing but stadium clubs to release and they just keep pushing it back on him I'm gonna lose it He's brown Nick Chubb That is Jalen Petrae like Willis rookie Cleal Shakir Nicoby Dean 24 out of 99 We've got me Cole Hardman on the Jersey auto 78 out of 99 nice one there Congrats on that there Chris and my home is vestige very nice Put revolution Chinese new year it is one I Legitimately think I've heard Vaughn talk about stadium club since like Since like June yeah All the guy wants to be released Chris Olava Jesse Lucchetta Duffy there's Chris McCaffrey to 249 We've got Malik Willis Year one auto Boom there we go Chris. Congrats, buddy Whoo, baby. There it is. That's what we were waiting for There it is congrats man. Nice Malik Chris year one Malik, baby. That's one of the best year ones you could pull right there to Chris nice hit buddy. Let's go Heck yeah, we'll mag that for you my man and a sheesh mark Andrews nice one there Sheesh Andrews that'll do it for your break there Chris. Thanks again, man. Appreciate the support We'll get those right out to you my man