 So, as Ian said, I'll be talking about this OECD work that I've chaired over the last couple of years. We published a report in the middle of this year, which is linked in the notes for this session. And so most of what I'll be talking about comes from that report, so you can get original citations and diagrams from that, etc. The aim of the report was to make recommendations to policy makers, because that's the level at which the OECD works. Every year the Global Science Forum brings together national departments, Australia is representing those discussions to understand where their areas of interest are, and they convene a number of these expert groups to work on a particular issue for a couple of years and to make recommendations to policy makers. So the contents of the report was firstly to look at what kind of data actually existed about what's needed in terms of a digital workforce in research, make some recommendations in around five focus areas and makes them to a number of actors, including universities and governments. Whilst this work started more than two years ago, it's worthwhile noting that COVID-19 has actually highlighted the importance of it, and I hope some of you are seeing this in your workplaces that we now increasingly understand the importance of digital skills for everyone, but also for the research sector and the need for open science to enable that. One of the key questions when we started was what do we know? What's the evidence about the need for a digitally skilled workforce? And I'm sure most of you on the call today share with me a intuitive understanding that we are in desperate need of that, but also appreciate that sometimes it's hard to find the data to substantiate that. So we did some looking around for what did exist, and this is a cross-section of a few of them. So for example, the European Union had a study that showed that there was a cost of not having fair research, and therefore that having better digital skills would enable more fair research. Now, there was a study done by the US, one universities, which are research-intensive universities, which found on average each university only had two data librarians per university. And some work that the DC Commission and published last year showed that in Australian universities you might have one research data manager to 65 researchers and even worse for software engineering. We found some other studies that showed how important a number of researchers said by the digital skills or the ability to use some types of digital tools were. There's some samples there that are all detailed in the report. To move our work forward, we did some in-depth case studies of 13 organisations that were engaged in best practice, and ARDC was included in that list, so that we could identify both commonalities across them, but also draw out specific examples of where organisations were doing things differently and having success. Our analysis found that there were five key focus areas that need to be considered. So if we look at that diagram in the top right, there's a light blue backgrounded section called defining needs, that we need digital skills, frameworks and roles, and this is where the OECD work had really started from. In fact, that was the initial focus in itself. And as we continued our analysis, we realised that was only one part of the puzzle, and there were four other key pieces. Provision of training, community development, career paths and broader enablers in policy, et cetera. In terms of the first area, I think we've all seen different variations of how to define the various roles that are emerging and what they encompass. This was a very simplistic overview that we came up with. You would have seen in arena slides a much more complex one. I am sure there are many different ways to represent these different roles and their overlaps as there are people on this call. So this was one way to delineate it. The region of training was an area that we highlighted strongly because whilst there has been conversation for now a number of years about how we need more skilled researchers and research support professionals like data students and research software engineers, there's actually been very little thought about how to provide the trainers that will enable that upskilling. And interestingly, also some silo development between the development of those trainers and the development of people who can teach undergraduates or masters program in data science. So that's an area that still needs a lot of thought. Community building was also strongly identified as important. That it's not just enough to upskill people. That people need to identify with other people in the same role. They need communities where they can engage with those other people, create networks, share knowledge and learn from each others. And that those kind of communities are needed in a wide range of areas, including the digital science leaders, that as these new roles keep emerging, they need, if you like, to be able to find their tribe. Career paths and reward structures is an area which I'm happy to say has received a bit more attention over the last year, but certainly equally important. Again, it's not important. It's not enough to just have people in the research sector with the skills. They also need to be rewarded for doing so. So the report then makes recommendations for a range of actors from national governments through to universities and research institutions. I'll just go through a couple, but you can look at the document and look at the detail and maybe some of these would be useful for advocating within your own organisation. First of all, we made one overview recommendation to any organisation that it would be useful to understand your own digital workforce capacity in terms of a maturity model. This is a very simplistic maturity model, but when we developed it about six months ago, we couldn't have named any organisation or country that was at level two, that was looking at all of those areas. There's been a lot of organisations at level one, looking at some of those areas and some of them are best practice in how they address those. It was difficult to find an example where someone was looking at all of those areas and particularly in a coordinated way. In October 2020, I'd say possibly that is now emerging that we could find examples that are looking at all five and beginning to look at the coordination across all of them. One of the recommendations we made to national governments was that there needs to be an understanding of the importance of all five areas and that governments could support analysis of national needs and responses to provide some kind of national strategy. It would be interesting to consider how Australia might address this going forward, particularly something like the National Research Infrastructure Roadmap Proceedings next year and if it includes a skills section in the same way that it did in 2016, it will be interesting to see if some of this begins to get picked up. There are recommendations to universities on some points that again are probably fairly obvious to most people on the call. There needs to be provision of training. There needs to be development of new career paths and there certainly are some examples of organisations in Australia that are looking at that and that strange looking graphic down the bottom is a screenshot from some discussions that have been convened across Australian universities by the University of Melbourne and University of Sydney on what they call third spaces, the people who aren't exclusively researchers or exclusively professional staff within universities. So that's a conversation worth being a part of if this is an area of interest for you. A few other initiatives to be aware of, if you haven't come across them before, there are organisations that focus on training like the Carpentries Internationally and have a strong presence in Australia. There are organisations that look at career path developments such as the Society of Research Software Engineering and there's a chapter for Australia and New Zealand. The RDA has an interest group on professionalising data stewardship, GoFair have worked as well. In the final logo there is the Academic Data Science Alliance, which is yet another focus mostly US-based but international and relatively US organisations share how they are developing best practice in a number of these areas. Australia did want to look at probably the country that's leading in terms of national initiatives. Netherlands is the guiding light and they have a fantastic white paper called Room for Everyone's Talent. Netherlands have the advantage that they only have five universities. So it's a little bit easier to get them moving towards a new future. In fact, Netherlands have committed that in five years time those universities will be using open science criteria as their main means of assessing research outcomes. There's a few other examples there from US, UK and Latin America who are also doing interesting things. I probably should add that probably every country is doing something interesting in one particular part. That's just an example of a few. Also, it's useful to be aware if you haven't come across some of the international principles or policy instruments that sit around all of this work. Dora of the San Francisco Declaration is an excellent piece, although only one Australian university is signed up to that, the University of Melbourne, although there are some other Australian organisations such as the Australian Academy of Science who are signed up. So Bond Declaration is a good one to be aware of because the group of eight universities all signed up to that. So if your university is a signatory, that might give you some leverage to ask internally what your university is doing to achieve that. And the Hong Kong Principles is even more recent, but useful in that it provides and that's what the diagram is on the left, some sample indicators that could be used to evaluate research assessment outcomes in place of the traditional impact factors, et cetera. Other international works, there's an Open Science Registry being developed. There's an event at RDA on that next week. Irina's talked a lot about the European Open Science Cloud working group that I'm also involved in, and I would highlight in that. She talked a lot about one of the strands which is looking at competence centres. I would highlight to Australia that language is now widely accepted in Europe and increasing, and it would be worthwhile Australia considering, Australian organisations considering if they want to start utilising some of that terminology as well to make what they're doing more readily recognisable by the Europeans. The knowledge exchange openness profile is another good example looking at how we can actually record what people's research outputs are in a range of digital objects and how that can be integrated with your awkward ID. And that's all the examples there. So finally, just a question to pose to you all. Irina mentioned that the EOSC as a whole is developing a document called the, and I'm going to forget what the acronym stands for, the Strategic Roadmap for Innovation and Assessment or something that's not even close. Maybe Irina can type it in. Anyway, she mentioned this document that's being developed that provides a roadmap on how EOSC is going to be moving forward over the next couple of years. And one of its key goals is that open science becomes the new normal. So I just end by challenging you all to think about how your organisation is moving towards that goal and how you can support it to do that. Thank you.