 Professor Richard Kinston, talking about NERC's Digital Solutions Club. Thank you. Thank you so much. Thank you. So this is a double act. So yourself, Nuran, Dave Topping was here yesterday. He's not feeling too well, so he's headed back to Manchester. Well, so those of you at the digital gathering, I think it was a cold out last year, in Birmingham, you'll have heard me speak maybe about what the NERC Digital Solutions Program is all about. And we're kind of a year on now from that, and we've made quite a lot of progress. What we've been doing over the last 12 months, since that last meeting, is going around the country talking to users. And just as a reminder, the focus of the NERC Digital Solutions Program is to make all of that 40 plus petabytes of NERC data more usable, findable, discoverable, accessible by non-academic communities. So it's quite different to a lot of other things that have gone in in the past, because our primary focus is on those non-academic communities, people in local government, central government, regional government, Quangos, environmental charities. And what we've done for the last, well, overall last winter, working with a community interest company called Open Data Manchester, I think some of you attended those workshops, is basically ask that community, what problems do they have in using data, and in particular environmental data? A lot of them had no idea who NERC were, so we weren't sort of saying, have you ever used NERC data? So they didn't know who NERC was. I'm not going to go through all of this. But the primary focus there was to sit them down in a room, in tables, and we use a very manual, paper-based method to collect information from them and understand what their problems were with using data. How could they, what were the challenges with integrating environmental data with other forms of data, social, economic, health data? And what were the kind of challenges in terms of using tools? What sort of tools were they using? So one of the most surprising facts from me that came out of that was people in certain organisations who had laptops so locked down they couldn't install the latest versions of a piece of software. They were using their own personal laptops at home to do the work that was part of their job. They were using four-year-old laptops. So one of the key things that came out of this is this digital solutions hub that we are building, it has to be some kind of web-based portal. So what we're doing is building this thing which is not just a big data portal, it will be sitting on Jasmine and have that power of Jasmine. So this again is something that these potential users of the digital solution. So it's not the kind of computational power they've had in the past. So there's a lot of modelling on all of this data integrating their data with others. Now what I'm going to do now is pass over to Nora because the program folks listen to talk. So Nora's going to take you through those kind of findings from all of those workshops and then I'll just finish off at the end with where we're heading next. Thank you, Richard. Okay, so the first thing that I'm going to do is just reiterate on what Richard mentioned and what we call the user needs strategy. So basically it was a multi-phase strategy. So we went through a scoping phase like 18 months ago we started that and then going forward to the online workshops where we actually asked users about nerds. So that was the higher level scope. And then we went through the data collection that Richard mentioned with the workshops. So those were 12 workshops across the country. We did speak to a lot of people and it was very, very detailed inquiry. And then we took that into sort of more detailed personas and scenarios identification phase. So that's the analysis phase sort of. And we got a lot of information out of that really. So it was surprising how much information we can gather from all of the sheets that were literally written on paper on the workshops. And then we are currently at a stage where we are taking all this analysis and putting it as requirements and citation for the hub. So basically taking all the information from the qualitative side of it towards the not so small box over there which is software development. So it's a huge process to take all this input as requirements and citation. And the idea is to have this as an agile process going through acceptance testing and then going back to the requirements and maybe eliciting more requirements and gathering more information with the users. So that's basically the approach that we're taking and it's gonna continue with us until the end of the project. And then once we have all the information from the workshops, we started asking ourselves very simple questions really. So who are the users that we want to target? What data and tools do they already use in order to capitalize on that? What sort of workflow do they already use including the pain points that Richard mentioned? And then how can the SH improve that workflow? In order to do that, we went through when the last thing actually is what we're working on right now which is the requirements and the citation and all those quest questions lead into the requirements at the end. In order to answer two of those questions, we have the report that Richard mentioned and it's gonna go out very, very soon. And it has different types of personas, different user journeys, seeing how different users use the data and what kind of workflows go into that and I'm gonna be speaking about that in a bit. The other thing that we did as well was a network analysis or a data ecosystem analysis where we started looking at who is using which tool and I'm gonna be talking more in detail about this in a bit as well. So basically all those inquiries together would lead into the design requirements for the hub. Those are some very key insights from the report but this is not everything in the report. It's actually basically only the gist of it. There is a lot of detail on what the users need included in that report. So basically the main outcome that came from everybody that attended the workshops is that there is a lot of data. It's on a lot of platforms already and it's quite hard for users to get the gist of all the platforms that are out there, all the data that is available and the user experience going through finding the data has been quite hard for almost everybody that we've spoken to. So basically going through multiple clicks, for example, in order to get to a certain dataset, but then once you get there, you find that it's licensed and you can't access it. So it's that kind of process that might need to be made better for the users and the idea of having to go through a lot of different websites and a lot of different platforms to get the data that you might need. That led us to key requirements. Again, this is only the gist of what is in the report. Much detail is included there. So basically if we say what do the users want generally to see on the hub, that would include accessing the data that they need in the easiest way possible really and taking a sample or seeing the sample of this information so that they would sort of know whether this information and this data is right for them or not. And then following that tracking the work was really important for them as well. So tracking the work and the resources that they've accessed maybe in the past so that they can reiterate on working on that. And one of the very important things that were mentioned they need to not duplicate the work and the effort that was done whether by themselves in the past or by others already in the field or in the same field. And the last thing is access to analytical tools whether and the idea of having consistent analytical tools and maybe support on computational power as well. And all of that would relate to combining their own data with already existing data. So a lot of the users had already access to a lot of data sets from their own organization's sensors and they wanted to combine this with a lot of other data sets but they needed to go around and find them before they can actually start cleaning them and so on. Which takes me to the next finding from the report which is basically everybody that we have talked to falls somewhere on this user journey. So this is a one user journey which takes the users from the idea of yet defining what they need to solve as a problem and then getting the data that will get them there and then analyzing that data and then showcasing that data. This could be to colleagues within the same organization or to policymakers for example for local authorities or central governments or maybe the public even but then there is a last part about managing the data. So managing iterations of the data managing additional information and analysis that they might want to add. And as this has been very common across everybody that we have spoken to some people would be less technical some people would be more technical but they would all fall on that line. So that as well helped us to start understanding another layer of what the users need and the other output was the personas or what we're calling the archetypes as well. So we started dividing sort of or well, some of the users would fall under multiple archetypes sort of but we started understanding sort of what are the different types of users. For example, the more technical users would fall under the analysts or the investigator where they are trying to solve a question or answer a certain question with the data. Some more managerial scales similar to the leader for example, where the positions in the organizations that want to make sure that the data is used properly within their organization. Some are more focused on the data quality. So that would be the users related to gathering and monitoring basically. So they're related to the data collection, GIS specialists as well and authors of the monitoring framework. So that will include policy offices at local authorities and similar positions. I'm not gonna go into much detail there but it's a lot of information again in the report that should be out and shared soon. So that's basically the user journey that we have seen types of archetypes of people that we have spoken to. And then the last question was trying to understand and dissect sort of what kind of data is used by which uses. So this is where the network analysis or data ecosystem came into play. So we started looking at users as nodes in a network and the data as the currency between them. So we started looking at what type of transformations that would happen to the data because usually users will get the data and then do some sort of analysis on it or cleaning on it. So there are processes that take place there and the idea was to start looking into opportunities and finding overlaps and doing so taking into consideration the archetypes and taking into consideration the types of organizations of each user. And the idea here is to get that part specifically would inform insights on the use cases. So that's basically delivering business values for the users. So on top of understanding how the users would go through the hub generally those would be specific services that we would provide. This is again a qualitative research. However, it's quite a robust dataset and it's interactive. We use it generally for the internal use of the team basically to start looking into use cases. So that's just a visual of the network that we have right now from the workshops. And when as it stands it's quite overwhelming but what we use it for is to basically filter out only for example data that was generated by central government organizations and then see who is using that data and then whether we can make that workflow better and easier specifically for those datasets. So that's where we're using that. And with that I'm going to leave you with Richard again for the next steps. Thanks. So we're at the point now where we were hoping we'd have had this report published. We do have a Word version but Open Data Manchester make a very shiny version of that. If you came to a workshop you'll get that in your inbox in the coming weeks but it will go on our website. So if you want to read 67 pages of that diagram and not understanding what are we potentially using using the data form or what they want to do with it you'll have access to that. So the next steps really we'll be following up with those 100 plus users going back and interviewing them asking them some more detailed questions. In the background our technical team we've got six RSEs and the systems architect and we've just today advertising for two infrastructure engineers. So if you've got any friends or infrastructure engineers send them my way that can come and work with us. We're building the hub that's going on in Kaulal in the background. So by autumn we hope that we'll have an early version of the actual digital solutions hub. We're building that on the Esri ArcGIS Enterprise System. There's a version that we're building a developed version in Manchester but the full working version will sit on Jasmine. So that gives you a GACC to a lot of those a lot of the data and the computation power. The other important if you came to the workshop you will have early access to the hub so you can start to try and break it and tell us what doesn't work. If you didn't come to a workshop but you would like to get the early access to that do get me a touch you can sign it through our website for our newsletter we'll add you to our contact database. So if any of you are keen to get your hands on this and the other thing I thought just to say was that a lot of you have presented what you're doing in the last couple of days into the new tools, new data that you're developing if that data you're creating is going into one of those five NERC data centers that data will come into the digital solutions hub. So I've spoke to a few of you over the last couple of days and if some of you have got other ideas about how you might want to collaborate with us so integrating the data you've been generating the tools we can then bring those into the hub because that's the whole purpose of this. It's about making all of that NERC data more usable to wider communities and what's great for you about that is that then ticks that impact box because we'll have a way of saying organization X actually use that data that you generated in that project that was funded by NERC. So further down the line when you're doing your REF 3037 or whatever it will be called your impact case over the next coming decades you will be able to trace that back to the fact that someone in death row or someone in CPE or a natural resource to Wales actually used your data and your tools. So keep in touch, you can sign up for various things if you've probably seen our roller banner out there pick up a pen, get a flyer you can follow us through the website on Twitter and all that kind of things and if you get signed up onto our newsletter we'll keep you up to date and you can also as I say get early access to the hub that we're building and I'll finish there. Very much, very interesting. There's a few questions that have come up already. Have you looked at all at the possible changing uses in the future that you've tried to do? So part of what, so the idea is Simon sat here so it's that we hopefully become a national facility and that we would get then another five years of funding if we don't make a mess of all of this. And the idea is that this user engagement will not stop. We will keep doing user engagement because the users change and users come in new policy changes. So we want this hub to keep reacting to that. So I think you always do user engagement in some form. So adapting as you go. And Carl says it appears you've done lots of good user research. Have you mocked up prototypes to sense check you your minimum viable product? Yes, to some extent. So what we didn't want to do in the workshops was go along with mockups because a lot of researchers that if you go along with a mockup to one of those workshops users then focus on the mockup and they sort of go away thinking, oh, it's all about this. And we didn't want them to be swayed by, oh, it's obviously just going to be a GIS to be honest. Maybe this had time savings in us. So we didn't present them with mockup. We gave them some flavor and some of you value it. But we didn't want to go down that route because that can steer the conversation and it pushes you down a particular direction. What we are doing though is developing the first version in the autumn. Those users will have access to it and play around it, break it, tell us what does it work. And so it looks like from the work so it's just a huge amount of information. Can you just say a little bit about how you filtered it to get to the important bits of the quantum digital? It was actually a lot of work done on that. A lot of that was done by ODIM as well. So I think it was done, she said. And the idea was to start with her and now different use cases for the workflows and then start gathering them together. So who is saying what? And then gathering everybody who said something similar and everybody who said similar barrier, for example. And then taking that through to, okay, so this is kind of an archetype and that's and that's where the journey came into play. But then what we're currently working on is adding sub-journeys sort of that would fit to specific archetypes and that would make sure that we're actually developing certain tools or use cases for that specific archetype. And that was, yeah, very interesting. Thank you very much. Thank you.