 Okay. Hi everyone. Good morning from sunny Vienna. This is the University of Vienna. This is where Monica's and mine offices are. So at least this way you get to see and come visit us at our lovely historical university building. So my name is that is a color bar. I'm the data stewardship coordinator at the University of Vienna. And joining me is my colleague Monica Bagman. Monica. I'm Monica. I'm one of the data stewards. And I'm also one of the students in this certificate course. So this is my role today. Thank you. So as Monica was mentioning she is taking this course currently and I am the scientific coordinator of the course. So today we will let you know a little bit about how we went about developing designing the curriculum developing the certificate course, and also a little bit about how it's going currently. And Monica will let you know a little bit about her experience from the point of view of a of the course participant. And we will give you a few pips or food for thought when you're thinking about perhaps developing a similar program at your own institution. So let's jump right in. So why do we need a course specifically for data stewards. Many of you, I'm sure are familiar with this quote by Baron months that we will need to educate around 500,000 data stewards in the EU alone to support researchers with various data stewardship research data management as these are deemed to complex and time consuming to leave to researchers. So we're trying to professionalize the tasks of data stewardship and make this into an individual role with the recognition that it deserves. The last question we asked ourselves when developing this course was, what are the typical tasks of data stewards. What do people who are currently in data stewardship roles, typically take on. If you find out more about that we conducted interviews with data stewards from various countries. We also analyze job listings job descriptions, and we came up with these five main areas of data stewardship tasks. On the one hand in the in the right hand corner, we have the advising the support of researchers, helping them setting up sustainable RDM workflows and helping them drafting for example data management plans. So that's kind of one of the major major areas. Then we have, when we move down we have the requirements engineering and generally the topic of needs assessment because we're trying to support researchers. The way they need to be supported so for that we obviously need to look into the needs they have in terms of research data management. And that in the bottom we have the image of a bridge. So that's kind of the image that comes to mind very often when speaking about data stewardship. And it just symbolizes connecting researchers on the one hand with research infrastructure or services that are located at centralized on the central level at a research institution. And just building that sort of bridge and having that bridging function. And then we also have the area of doing training so very often data stewards would offer training on open science on research data management practices to researchers and students. And then the last image is to symbolize networking being involved in various national international initiatives and working groups. So these are the kind of the five main areas that data stewards that are currently active, typically take on. From that, we moved to the question of what competencies do data stewards need in order to be successful in picking up those tasks. And we've have these kind of four areas for major areas of competencies. The national competence is probably no surprises there. These the students need quite a large wide area of skills and knowledge and from many, many different areas. So we're obviously starting with research data management and we have open research open knowledge topics, data formats file formats. We also need some knowledge of data security but also legal and ethical knowledge is really relevant to data stewardship practice. And we moved to the methodological competence so this is what I was already mentioning this this sort of bridging function and the ability to translate the needs of researchers to research infrastructure and policy. And but we also have skills such as being able to give a good presentation or being good at conflict management. And then we have these two areas personal and social competence. So in the area of personal competence. We have quite an extensive list as you can see. So data stewards need to be quite results oriented here is also tolerant to practices and various disciplines, and the one that most data stewards always pick up on when I show this, this graphic is patients. I'm sure that Monica would agree with me that being patient is quite key to being successful as a data steward. But generally the most probably the most most important and helpful competence and skill a data steward can have as communication. We've seen a lot of the tasks and a lot of the, a lot of the activities that they just take on kind of focus around communication. So this is very much key to being successful in those data stewardship roles. So we haven't really looked at the topic of data stewardship training and education and isolation. At the University of Vienna we took a more holistic approach to the topic and we decided to set up a formal data stewardship program, which consists of two parts. On the one hand, we have the certificate course. On the other hand, we have the certificate course data steward, but we also started our own data storage network, which is very similar to to the ones that I'm sure many of you are familiar from the Netherlands for example, where we have one coordinator at the university and then we have embedded data stewards on the level of individual faculties. So in our case we're currently running a pilot for, for our data storage network with three embedded data stewards at two faculties and one research center. The University of Vienna is a very large research institution. We have 15 faculties and five large research centers that are considered on the same level as the faculties. So ideally we would have at least 20 data stewards. As we all know it's not that easy to create new positions within a university and we were very lucky to be able to convince our administration that they fund this three year pilot with three data stewards. And hopefully we will be able to get more data stewards in the future. But we didn't want to just hire people to come and work as data stewards, but we really wanted to, you know, support them in order to acquire all of these competencies that I was mentioning before within their first year on the job. And that was very much one of the main reasons why we developed this course. Let's chat about it. We've designed the certificate course data storage around kind of three main guiding principles. So of course we have the competence acquisition on the one hand. But we really wanted to support peer to peer learning, because this is a further education program so mostly it's it's professional joining us who have work experience and this we want to we wanted to really honor that work experience that they have. And the skills and the knowledge that they've acquired through their previous training or or degree programs. All of that was very much with the goal in mind to develop a data steward community and have our emerging data stewards become a part of both the data stewardship community and Austria but also internationally and ideally globally. So, a few of the basic facts about the certificate course. As I was mentioning it is a part time further education program. And it's in part based on a course called data librarian, which we used to offer several years back, but this course was open as the names and suggests to librarians or information professionals only. We very much wanted to expand on the target group because data stewardship is not only being done by librarians. And what we also considered what were the results of the fair data Austria project, which was a national funded project that ran for the past three years, then very much brought the topic of data stewardship to Austria. And that's where we in that context we created all of those tasks and the competencies that are with you before. We also collaborated with similar further education courses, such as data train or the certificate course, RDM certificate house goes if they am from Germany. So, once you've successfully finished the course you receive an official certificate of the University of Vienna. It is conducted in English and it takes two semesters and that amounts to 15 credit points. So as to our target groups, we wanted to keep it as broad as possible and just be very open to to again people from various paths of life and just approach this topic of admissions. Very holistically to conduct a holistic review. So we are trying to target both active researchers PhD students postdocs, who kind of want to make a shift more towards more towards research data support or just research in the digital channel, but we are also trying to provide an opportunity to up skill current research support stuff in order for them to take on this new role. And the course costs 2950 years. Our main goal here is to prepare both existing and new hires for the challenging neural of data. So let's have a quick look at our timeline. We started in 2021, and that was very much part of this third data Austria project where we developed the initial concept for the course and we developed the curriculum. And we've conducted several feedback rounds with experts on on research data management data stewardship, also research data management training education, in particular, and we've worked together very much with experts with from the third year project so it was very much designed with the within the framework of the project and kind of looking at the situation at Austrian research institutions. And this was invaluable in further developing the curriculum, and then also starting the formal accreditation process within the university. So in 2022 we were able to complete this accreditation process, and to start setting up a marketing plan PR plan, and to also open the online registration for the first round of the course. And kind of at the same time we were contacting instructors lectures from Austria and other mostly European countries. And together with these experts we were detailing this basic curriculum and we were kind of completing it in order to start the course for the very first time in October last year. So the way the course is designed it's set a split into five modules. All of them are obligatory. So we start with the first module, which very much introduces the topic of RDM and open science to the participants. And then we have the second module which covers the basics of it applications and some data science or data driven research. And as you see in the, in the picture on the right hand side, these two modules very much build the basis of the course. And we kind of touch upon a lot of different subjects that we really cover in detail, and the third module, which is called fair data and the research data lifecycle. And then we move to the fourth module, which starts translating all of that knowledge that the participants have acquired throughout the first three modules into data stewardship practice. So we're talking about developing RDM support services and and kind of basics of teaching and doing training, which will then really be used within the fifth module, which is called data stewardship and practice project work, where the participants complete either an individual or a group project. So I added some of the feedback we've received for the first module, which has been overwhelmingly positive and generally the feedback has been really, really good. And we're really happy with where we're at at this moment, kind of in the middle of the third module, or really towards the end of the third module currently. We'll see how it goes. But so far so good. Here are just a few details, few of the topics that we're covering within the individual modules. And now I will let Monica tell you a little bit about how it's going for her and what recommendations she has for you. So as we mentioned in the beginning, I'm talking as a participant in this course as a student and also as a person who is now a data steward and also has been a data manager for five years before that. The first point is language and internationality. I especially enjoy the internationality of the course. The various countries have the same challenges and many initiatives in Rdm are located on a European or even more international level anyway. So it's, yeah, this is a good viewpoint, I think, and having it in English is also a good training even, or maybe because it's not the first language of most of us. So, but we will have to talk in English in our jobs with researchers who are not can speak the country's main language so it's a good training. And meeting in person. Doing the course online has advantages not only in pandemic times. It makes attending for people from five way easier however you define five way it might be to cities away or five nations away. So thinking of those people that pay for the course themselves we have some of and it would cost a lot more if they had to come for every module and stay here and so on. And also for people who don't like speaking up in a large group it might be easier to add or ask something in the chat for example. And meeting in person at some point in the course is central for establishing a community because we Terry's already mentioned the peer learning. So for the sense of community. It's, I think, ideal to meet at some point in the course in our case the first module, which is a whole week. And this was in person. And from another course I attend is making a personal introduction videos only two or three minutes just what you do professionally and also something personal. So, not only the participants can get an impression of the other people beforehand, but also the lecturers can watch the videos and so we are spared round after round of introductions that everyone knows by heart already. The building upon prior knowledge is, I think, an important thing to discuss. Because a colleague and I discussed if we should have some. If people should have prior knowledge in data management so you could already start that it may be not higher but more practical level. And I also attended the predecessor course the data library in course before a few years ago, and here a deeper training in library science or at least experience in library work was a prerequisite. And this has advantages, but in the ongoing data steward course we come from various backgrounds so there are researchers it stuff technicians librarians people already working in research data management or even being data stewards already. And I think we should value the individual experiences and knowledge and that the group benefits from the variety. One example, especially as a data stewardess I benefit from the questions the researchers in the group ask, because these are the questions that also my researchers will ask. So, this is the, I really like to see the point of view. So building upon prior knowledge, yes, but not building upon prior data management knowledge. Maybe you could send out some introduction and literature to read beforehand, but I wouldn't make it a prerequisite to be already data management. So as I mentioned the first week took place in presence. And on the first day we came into the room and had seats assigned. And this was a bit strange because you know everyone wants to sit in the back. And then we discovered we were already assigned to body groups of five people. And these groups were not randomly put together, but they were chosen carefully so it's. And it really worked great. So we have my group, for example, we have two researchers from different areas. I might background this librarian, there's another librarian, but it's a medical university. So in another field of studies, and also artist and it technician art researcher and it technician. So it's a really good group. And we identified quite fast also with the members and with our group and some advantages I see people who might feel some people might feel unwell in large groups of unknown people. And so they have this smaller group to start talking with. And also it's much faster if you need groups for some group work within the lectures because you already have your assigned group. So and this group stays like that for the whole course. As I know not from this course but from other courses I have inside there might be conflicts in such a group. For example, misunderstandings or different working styles coming together. And so you should be prepared just in case to moderate some conflicts, especially if some working groups is crucial to complete the course so if they have to work together. In our case the body group we can use it to exchange experience and so on and we do some group work but it's not our last project for example is is an individual work and not a group work, but just to consider when you build some groups like that. And the last point I want to make is that as a student I like to have this international course, which might be supplemented by country or region specific add-ons. For example, expanding on EU legislation or national research funding structures is important, but not necessarily interesting or useful for all in the group depending on the country that coming from. So this might be dealt with in kind of an add-on. So coming back to my first point, the internationality. I don't really think that every country needs their own complete course, but could offer some add-ons and other modules for example. And so I invite you cordially to join our course and then design some country specific plus things. Okay, Theresa. Thank you Monica. So now that we've heard a few tips and suggestions from the point of view of Monica as a participant as a student on the course. So I have a few things to add from my perspective. So when you're designing a course for data stewards, it is a good idea to let the program reflect the global data steward community. It's trying to make it international both in terms of the instructors, the teachers you invite to teach on the course. So try to think outside of the box, we all know the big names in the RDM community, but there are a lot of experts out there who might not be as visible as some. And they might have a lot to offer and they might really jump at the opportunity to be able to share their experience and their knowledge with the new next generation of data stewards. So we really can recommend developing a holistic admissions process. So really try to think about the experience your participants have, you know, is this something that's going to benefit the group. This experience that they bring is it like unique and something that you know nobody else has. Because as Monica was mentioning, this has definitely been the most beneficial within our course. For, you know, within the group of the participants but also for us as instructors as trainers on the course. We've been able to learn a lot from the participants as well because they bring such diverse perspectives. I mean now, both looking at, you know, various research domains, but also trying to consider people who perhaps don't have that sort of formal education or don't have advanced degrees. Because yes, currently there are many data stewards who have a PhD, but there's so many more people who take on data stewardship roles or tasks of data stewards who perhaps have a high school diploma. And they might have 10 years of experience and you know supporting their department as, for example, with with software development. And they might not have a PhD in computer science, yet their experience would be invaluable within a course like this. So just really appreciating and trying to utilize, you know, the diverse perspectives the participants bring to the course. And yeah, as Monica was mentioning, we are happy to talk to you about possible collaborations. So with our course, or else you can always just sign up and come to Vienna in October. The registration will open on April 17 so very very soon. And if you're interested, you can check out the website and sign up for one of our information events or just sign up for the newsletter. So we will let you know when the registration opens. But for now, we just want to thank you for listening and we're really excited to talk to you and answer all your questions.