 Hi, everyone. Thanks for coming along to this fourth webinar introducing the institutional underpinnings draft RDM framework. I probably do a terrible job of introducing myself on each of these, so I might actually do that this time. I'm Nicola, I'm the program manager for institutional underpinnings. I've got a number of members of the team here with me as well who'll be helping out. I'd like to start by acknowledging and celebrating the first Australians on whose traditional lands we meet. I think there's a number of us here from all across Australia and New Zealand, but for me in Perth, that's the Wajatmonga people, and I'd like to pay my respect to elders past, present and emerging. So, today I'll be giving you a bit of an introduction to the institutional underpinnings program and the framework that we're developing, and mostly what we're here for is questions and comments. We will be using a Q&A tool to manage questions. I'll give you a link to that in a second. We'll decide whether or not we really need to use it, depending on how many people we end up in here, and a couple of these we've used the tool, some of them we've just used soon. So, we'll see how we go, but yeah, I'll take questions at the end. And yeah, we're recording at the moment. As I said, the presentation part will be shared just for people who weren't able to make it today, but anything that you say or ask will be kept private, so feel free to say or ask anything that you like. So, yeah, we'll be using Mentimeter just to keep track of questions and comments today. It's just useful because it's got an upvote function, so we can get to the most requested questions first. So, you can just scan this or enter that URL, but I'll put this up again at the end when we actually get to question time. Okay, so ARDC is where we are running this program from. Our purpose is to provide Australian researchers with competitive advantage through data, and I would do that by accelerating research and innovation by driving excellence in the creation, analysis, and retention of high quality data assets. We do this under the auspices of the increase. So, this program is part of the National Data Assets Initiative, Institutional Underpinnings is part of the National Data Assets Initiative, and these are a set of programs which are designed to develop a portfolio of national scale data assets to do that work of supporting leading edge research. So, these large data assets is infrastructure, and the majority of the programs within this initiative are actually focused on the building of those data assets. Institutional underpinnings is slightly different in that it looks at the underpinnings that are required to actually put together and maintain those data assets with the acknowledgement that data is created in institutions, it lives and is cared for at institutions, and its institutions coming together that produce those assets. So, in order to create and maintain these important national scale data assets, we need to look to the research data management capability of institutions. So, our aim in this program is to advance university research data management together by collectively developing a university research data management framework, and the idea is that this framework should be able to inform universities design of policy procedures, infrastructure, and services with the aim of improving coordination of research data management both within and between institutions. And it's really important for us in this program that we recognise that universities aren't all in the same place in terms of research data management and they don't all have the same scale and needs. So, we're very careful here to make sure that we're not being prescriptive and saying everyone has to use the same set of systems. What we're instead looking at is trying to work out how we can have a more common approach to research data management. Something to point out is that we talk about the word framework, we're building a framework. This is a conceptual framework, so the idea is that it's a way for us to structure our approaches to institutional research data management development. And it's looking at places where we can collectively build an advance as a sector. We're not talking about a regulatory framework that sort of prescribes or constrains how you provide research data management. So, it's just an important focus to have when you think about the kind of framework that we're building. So, models of research data management do already exist, I'm sure we're all aware of a few of them. So, what are we doing here that's different? Well, we're really focusing on what we need right now rather than trying to create a sort of a perfect comprehensive model of institutional research data management. So, our focus is on addressing current needs and working out where we can make the most of working together rather than just laying out everything that is needed, although I think we've done a pretty good job of laying out what's required. So, we're aware that complete and perfect are impossible goals. So, the focus for the group has been what is valuable for universities right now. So, in this program, phase one has been the building of the framework. We're now in phase two where we're testing and collecting feedback on that framework and we'll soon be heading into phase three where we refine the framework based on that feedback and then present what we've developed back to the sector. So, I'll just take you through what was done in phase one to get us towards the draft framework that we'll be talking about today. So, we focused on Australian universities as major producers of research data. All 43 of Australia's universities were directly invited to contribute and 30 of those universities participated in an initial workshop where we talked about what we wanted the framework to be able to do for us and how we wanted to go about building it and then 25 of those units applied to participate and they were all successful. So, we've got a group of 25 universities who have been working together in this program and something that was really important for us was that participation is at an institutional level. So, we know that universities are very complex organisations but it was really important that although we had one representative, that representative had contacts throughout the various parts of the university that work in research data management and that there were internal structures, committees or meetings or whatever it was that allowed feedback from all of those relevant parts to feed into the program. We also have an editorial committee whose work is to take all of the content that's developed by those 25 universities and to actually get it down into some documentation that reflects all of the discussion that's been had and all of the outputs that have been created. So, we started building the framework by just collecting all of the ideas and challenges and issues that were sort of felt pressing right now to the universities who were participating and we then took those, all of those ideas and challenges and issues and we drew them together into themes which are areas of research data management that are really important for a university and what we did. So, those themes are the elements of research data management that are presented in the framework and for each of those elements we worked together to collectively identify why they were important for university RDM and then we ended up with 16 of those which is fantastic because it gives a really broad view of what's needed but in order to make the most of the resources that we had we had to focus in on a subset of those. So, we, as a group, worked out which were the areas where we could make the most impact by developing those out right now. So, these were the 16 framework elements that were identified and it was these eight that were selected as being ones where there was a current focus, where people were available to provide work into working groups and to develop these out and where we thought we could make the most difference. So, each of these elements was selected for development in a working group. We ended up with 95 experts being nominated from across the participating universities who formed these eight working groups and we, for each of these, the working group over a number of months identified commonalities and differences in need and approach across universities of different scale and research intensity and then they compiled best practice recommendations and advice and they also importantly looked at where currently either best practice wasn't identified where we still needed something to be done in the sector that no individual uni could provide and tried to pull together calls to action. So, what needs to happen next in each of these areas? So, I'll just take you through each of the eight elements quickly just to give you a very light definition of what each of them covers. We obviously don't have time now for me to take you through the content of the entire framework. I also don't expect you to have read it right now for this meeting but I'll give you a bit of background that might also help you to select which of the elements might be most relevant for you to take a look at. So, active research data management is about the universities providing the infrastructure for the management of research data during the life of a research project. So, everything from where the project begins and data is acquired or collected through to the end of a project where that data no longer needs to be frequently accessed anymore. Culture change looks at shifting institutional research data management practices towards where we want them to go, something more effective and this section covers both changes in the attitudes and behaviour of individuals but also how you shape and guide change in institutional processes. Policy, that's what it says on the turn, it's about the policy that lays out the principles by which a university manages research data and this section looks at suggested content for university policies around research data as well as approaches to implementation of those policies. Research data management planning looks at the ways that universities can support researchers in their forward planning of the research data management for their projects. So, this both includes the formal documentation of planning in documents like DMPs but it also looks at how else universities are active in the support of forward planning processes and how that can support good research data management to the university. Retention and disposal is quite an important focus for a number of our universities. It's looking at how institutions make decisions about what to do with research data after a project is over and it's a particularly interesting problem as we look at having to increase amounts of data and what we do with that storage burden long term. Open research and data publication acknowledges that there's a strong movement in research towards open research which includes making data fair and or open and the fact that there's an increasing call from publishers to have research data be in some way accessible whether it be openly or in a mediated way and looks at how institutions can enable and support that. Sensitive data is a broad topic. This group ended up looking at how the levels of protection that are needed are assessed. So, looking at the classification schemes that allow us to assess the level of sensitivity of data that's held at a university. And finally, support trading and guidance looked at how institutions can provide researchers with the knowledge that they need for good research data management be that through training programs, written guidance that's provided support services. So, quite a broad range of topics that were covered. So, we closed up that phase towards the end of last year and we're now in phase two where we're testing all of the recommendations and advice that were produced in those working group outputs and collecting feedback from the sector. So, one of the ways that we're testing this framework is that participating universities in the program are taking an aspect of that framework, an aspect of the recommendations and advice, and they are applying it to a project that they are running locally so that they can make sure that that advice really works for their particular circumstance. So, helping to make sure that we really are providing guidance that works for many different universities. Alongside that, we're also doing this broader consultation with people who maybe weren't necessarily involved in the writing of this framework documentation, which is what we're doing today. So, after this second phase closes towards the end of August, we'll then go into a three month process where we refine the framework based on everything that we collect and then we will present it back to the sector. So, today and this month is really about collecting your feedback on the framework documents. So, as I said, I don't expect you, it's quite a lengthy set of documents. I don't expect you to have read them all today, but you can access a draft, these draft framework documents on the ARDC website. I think that a link may have just gone into the chat. Yep, awesome. And below the links to those documents, you can find a template in an online form where you can submit your feedback. We really strongly encourage collective feedback. So, if a number of people from a group or an organisation have all been reviewing these documents, it would be great to get your views condensed into one feedback template. It's both helpful for us and also means that we can see where particular feedback represents the views of a group. But individual feedback is also very welcome. So, what we're interested in both in that sort of longer feedback template process but also today is your sense of whether the guidance that we're providing out of this program reflects your understanding of university's needs, whether you work in a university or with universities, whether it meets your own data management needs. And that's particularly interesting for us for those of you who may be either working in universities who weren't involved in the development of this or are working in non-university organisations that also have data management needs. This guidance was created by universities but we're curious to know how broadly applicable it is. And we're also interested for those of you who work with universities, what is it that you need that would make it easier to work with universities? Where can we create a more cohesive approach between universities that would make things easier for those who work with universities around research data? So, those are kind of our focuses both today and as you write your feedback. We're also quite curious about how the material could be most usefully presented for you and what steps would be valuable to you following the release of the final framework?