 Okay, thanks everybody for joining this committee call and we are kicking off now the the meeting. And we are sharing here the collaborative notes so if everyone cannot speak and would like to contribute in a written form or you can also directly type here. And, okay, so I'm giving the floor to Ali, to start this committee call. Thank you. I will follow up with a with a round table than Julia and thank you very much for supporting today's event Julia is actually participating at another event which is across the Atlantic. It's very early for her the moment but she insisted that she will be there because she really wants to see and take part in the discussion so thank you, thank you Julia. Yeah, so, I mean, let's start with, let me see with no particular order as how I see the participants list so please don't get offended it's not me it's zoom to blame. And you, you already said that you don't have microphone or. Yes, or audio, but Alan you're from EPFL, at least I know you so I can maybe introduce you. You can type okay good good let's let's let's do that. Yeah. This is a good test to see who writes quicker, I know I wouldn't be the quickest. I would fail. Yeah, from EPFL library Swiss Federal Institute of Technology in Lausanne, active in data management support yes and this is actually how I know Alan, like, we met two years ago I think we still have things to to finish reminded. But let's, let's see now with a new involvement of the software, we can definitely allow more things for the template. Where am I again let's open the list. Nice to see you here Alan. I see Diego Morgave. Please feel free to open my camera, whatever you feel comfortable or type. Okay, okay, I see, I see the chat from in red and not available for this meeting. No worries. You can always listen. Nice to, nice to also have you here. Yes. So, I'm Joachim Phillips and from Stockholm University. I've been working with research data management since October 2016. And in also with the DMPs with, in particular with DMP online service and in that function it has been very interesting to follow Argos on the side to to compare and so I tried to follow the development of this tool, but I have to confess that recently, I have been devoted to other tasks. So I haven't worked much on it, but I'm eager to catch up on what's new. So, thank you. Good. Thanks, Joachim. Then we have john from Spain. Hello. Yes, my name is Johnny with the. Sorry. Don't never mind that it's okay. From the emails. We don't have a pronunciation. I know. We are very little university in the northern part of Spain, the best country. And we have started a last course, talking about DMPs and a helping our researchers with with the DMPs, because the European Commission is asking them in the grant agreements. So we are very new. And we are, well, we have just translated the Argos to our language we have a not even. We have, we speak Spanish also but we speak Basque is our country language, so a regional language, I mean, and we are working with Ellie, and we are very grateful to her, because we she's helping us very much, but we are very new. So, wishing to learn as much as possible. And then I have changed Maria change. Maria Maria. Maria. Hello, everyone. And my name is Maria Codopini. I work with family. In our center. And I'm providing tests for Argos show the quality. Thank you Maria Maria is every day living for testing Argos and making sure that the quality of the software that we release is fine. Thank you. Thank you Maria so much for the dedication and enthusiasm also in your role. Then we have again sorry if I mispronounced your name. Saha. Well, you're not going to, you're not able to correct me, which is, okay, I'll go with Saha. I'm from a special advisor in data management from the Royal Dennis library in Denmark. And you're again, neither in the possibility to speak that's fine. No worries, but glad that you were able to make it and thank you for joining us. It's good to have you here. Then we have Stefania. Hi, everyone. I'm Stefania model. I'm engagement and training officer at open air. I'm involved in several open science projects and in particular, in one with Ellie that where we're working to advance Argos to include aspects related to reproducing reproducibility in data management plans. Nice to meet you. Thank you Stefania. Yes. This is an interesting thing. I'm very happy to, like I'm looking forward to share what we will come up with in this project with everyone here in the community. Let's see. We're getting there. Okay, let's see. Well, thank you. My name is sorry, my name is Teresa. I'm research coordinator at university library in Sweden. I've been in this field for, well, about one and a half years. Yeah, if it comes to data management plans, I do much of our teaching work. I'm not so much the person behind the surface building templates and those sorts of things. So we have so far used the impion line and we are excited to learn more about Argos. So that's going to be a very interesting journey, I believe. And yeah, I'm grateful to be here and happy to learn more. Thank you so much. Thank you, Teresa. And I see that Sahaa also says that they're also working with the impion line and would like to know more about Argos. So that seems to be the theme. Um, and we have two new people that joined while we were. Yeah, while we were doing the introductions. It's again taking it from alphabetical older that I see that zoom provides, are you a value though I made that. Hi, would you like to say a few things about you. Who you are where you work. What interests you. Okay, I'm from Brazil. I'm doing PG in Coimbra University. And I'm here to understand a little bit more about what you're doing about data because by my whole life I've worked in companies that manage enterprise data. That's why I'm here. Okay, we are focusing on the DMPs. Is that okay for you. Yes, I'd like to, let's say, and understand that what I can do knowing about infrastructure data infrastructure, I'd like to, to create a link between, let's say, data infrastructure with the DMP. Okay, I see. Okay, then you're in the right place. Okay, because I was, you know, confused maybe you're not maybe we're wasting your time but no we're not. Okay, you're okay. Good. Nice to, nice to meet you. Nice to have you here. And Paula, last but not least, I think you were, you entered later. I, hello, I entered late. Do you want, do you want me to give some context about the Portuguese about Minho. Yes, please, please go ahead. I mean, I know, but not everyone. Okay. So I work at the University of Minho, and we have an articles open DMP instance at the university within the project with with other institution a polytechnic project polytechnic institutes that we together are creating an open DMP instance for to have our Portuguese from their template and to in a long term to create a template for the, for the university also, among other services that we are creating to, to help researchers and to to fulfill their, their work within research management and in their projects. Thank you. Thank you, Paula. And another one, another colleague joined. Vicky, I see you joined now. Would you like to introduce yourself. Hello. Good afternoon to all. I'm a newcomer. I could say I'm Vicky from the Athens University of economics and business library information center. I am at the beginning of inverting with our course and all these topics. We have a regular cooperation with a in different themes here in Athens. And I'm happy to join you today. We happy to have you, Vicky. Okay, I think that's all right. Sorry, if I do I miss. Oh, there's someone in the waiting room. Sorry, I admit. I see. Hi, met meton. Hello, meton. Can you hear us. Sorry if I'm mispronouncing your name. Hi, meton. Hopefully you can hear us. Maybe if you want if you hear us if you want to introduce yourself and write some things in the chat that would be great to get to know you better. Okay, then. Unfortunately, we could not understand basket. I would I would like to be capable to do that one day though. Right. Yes. So today's meeting is, you know, we're celebrating this is an international and access week. Most of us have been both open access, moving to open science which includes data which includes software and all the different elements. And, again, I told you that I was, I am actually at the RDA, not in Vienna in Vienna is where my flight went, but I'm in Salzburg. And we had a very nice discussion yesterday in the session about the MPs which I really wanted to bring to our community as well and see how we can better support researchers and institutions also and funders and essentially what we can do in this ecosystem to promote data management and management plans and make it a tool that it is not like a pain for is not perceived as a pain or a burden from researchers. Yes. So I wanted to let me see. Another thing that I could mention since since you want to know few things that are happening. Opener got a project, a European open sense code project that focuses on creating the links between scientific knowledge graph data management and for assessment tools, and we will be working with the community to establish interoperability the interoperability layer that is needed across those different tools and piloting what we the outputs of our work. And then piloting them as a commons and then piloting them in different countries and different domains. So that's the project will start in 2024. Of course, I can every six months or once in a while, maybe in our October meeting which is a more of a discussion and celebration we could also bring things from this project that are relevant to the MPs into into our community to to be aware of what's happening also, but at the European level of course in the context of the years. I'm very excited for this project to start in 2024. And that means that this will influence also the developments in Argos and the open the MP software that is behind it because it will support some of those national and less of the domain specific but more national pilots. So maybe we can have like an idea of how the discussion will do the different things that the discussion could have like, we can save you things about the technical challenges that we would like to overcome. Maybe again this project could be a good opportunity to do that. The policy related issues like what do we feel that could be done from funders or institutions to support them, and maybe the more procedural who would like to start like with their their perception their experience and maybe their ideas of things that don't work and how to move it forward. Maybe if, if I can ask you here. You spoke about the project that we start in next year that open air is involved in the interoperability layer. Open air is coordinating it. Yes, maybe for some of the users that are here present the part of interoperability is still something that is difficult to understand. And what is a knowledge graph, it's not something that is known by all the users. So since today we have a lot of newcomers, maybe we can explain that this kind of jargon that for the newcomers is hard. But what is a knowledge graph, maybe is the first step. And then we can also explain what is an interoperability layer. Well, and knowledge graph is a database entities and links between them, let's say. So it's like, we, we get opener at least the graph that opener has maintains is getting information from funders from journals from repositories from registries of any type like protocols, data software, whatever it is, getting all this information, the duplicating applying some text data mining to ensure that Yeah, everything like everything is classified. Well, and then this them creates this huge, let's say, graph of entities and links between them like the entities that we have at the moment are projects, researchers, organizations, funders, outputs like data sets, publication software, the MP is available in other outputs that can, we can see all the links between them. And these are also searchable through the opener discovery called portal which is exploded opener that are you. And this is actually the instance of opening the software that is hooked in this graph and gets and gives also so it's a two way communication with this graph so we get information from the graph through some endpoints, shoot through some endpoints, and we make the searching of information for a repository where to deposit for metadata standard what metadata strategy use easier inside the template so that the researchers don't have to click to a link and go to an external research for example, and leave, let's say the platform. Ingestion retrieval it saved information easier and then we also make sure that when we publish something we send this information to the knowledge graph to this graph, so that we also enhance this graph with the information that the DMP holds interoperability. I mean, it's a minimum. We have a standard that we are using it's the provided by RDA the RDA DMP common standard. So I did here in the chat. And this will be extended. And also in the context of work that we're doing with Stefania in this part for reproducibility. So what, what the standard does is provides a minimum set of entities and properties that should be common across all different DMP tool providers, so that if we take the DMP and downloaded from Argos and uploaded on DMP online, for example, since many of you mentioned, then no information will be lost, not the information at least that the standard requires or requests, because DMP might have more information in it, but the standard has a minimum set. Is that understood. Okay. Yes. Yes, while I remember, I want to say. You asked for the problems with the person to DMP tools. I can think of a few. For example, DMPs. Research which outputs, yes. But is specifically for DMPs. There is currently very little in motivation or to publish your DMP. And also very few DMPs have kids, which is necessary to connect them to the, to the knowledge graph. So that's one problem. And another huge problem is that the most funder templates that that are present are are simply text based and not compliant with, with the, the RDA DMP common standard. So, so these are two big problems. I know there are attempts being made also in DMP online that we've been using to, for example, they've added recently research outputs and if you, but again, I think the motivation on, on the, on the user side and the researchers to, to, to put in something there is minimal. So, so there has to be some, some ways of motivating researchers to, and also, I mean, one way of doing that would be to offer better templates like, like in Argos, or so, and make it easier to fill out those DMPs. And what you're, where, where you're heading. And we appreciate that, but I think it will still, for some time still a lack in motivation for. So you're. Yeah, thank you. So your point is, has two different things. So one is the PIDs for DMPs, which is not very common. And we offer that through Argos that this is true. And we offer that also as a software, we follow the data side and the core vocabulary. And then the other thing is the, yeah, I mean the awareness and the incentives basically of researchers. Actually, yes. So today I was also in a Greek webinar. That was about providing support to researchers on how to deposit their data in data repository in a university repository. I had to talk, the first part of the session was talking about this, where to share your data, where to deposit your data, which is something that they can understand. Easier. You go there, you click upload, it's uploaded, there's a form, you add the title of the data, you know the license, click submit and then someone receives it curated and I brought in curated and then it's available on this data repository, right. Something that they can understand. But when we talked about the DMPs still seems to be like the, the topic that is very difficult for them. And I think it made me think at least that what we probably, apart from the tools that we have and we support and engage with researchers through the tools is to provide a curriculum or a sort of course or set of courses that breaks down the different elements of the DMP in a very like simple way and straight way so that they can digest it. I think I don't know if you have any examples. Teresa, you said you mentioned that you train in this topic, maybe you want to share your experience and examples that we could also adapt. Thank you. Well, we have. I would say we have good experiences from the workshops that we give. Our success rate is not 100%. So, if you look at our course evaluations, there are still people after a workshop who do not say that they do not know who to ask if they have questions about our DMP tool. But I think the majority of people feel that they, that they can write the data management then at least gets started. I think in the workshops that we give, I tried to explain that data management plans and research plans are different things. I have different structures that different points that go into these documents and those sorts of things. And one thing that I find important is giving them a demonstration showing how to use a template and showing them that it's possible to write a draft of the data management plan in about half an hour if one has a question-based template. And at this point, I would like to say thank you to Joakim because they were first with question-based templates in Sweden and they shared their template with us so that we could use it to build our template. And that makes the work to write data management plans easier. We cannot do it without free text. Not completely, but in many cases that makes work easier. We have not come to the point that we really can offer a tool for data management plan that makes the administration that researchers have to do easier for them. We have some attempts to do that. There is a project going on in the consortium of the Swedish National Data Services at the KTH and Chalmers. And they look into machine-readable data management plans, but with other tools. They have a DMP online and data storage business. So they have made some progress, but it's not ready to be rolled out to a larger audience. I've also seen a very nice example at a university college. They have a combined, they have a home-built tool where researchers can on the one hand write the data management plan and on the other hand report processing of personal data. So they do two things in one step and apparently that is very much appreciated. That is also one of the questions that we would like to explore. To what extent can we integrate the work to write data management plans into the administration of our university? Yeah, for different reasons to make life easier for the researchers, but also to get approval from other important persons at the university, our lawyers, security experts and so on. And starting from there, I think we can look how can we integrate other open science tools, repositories for instance. Yeah, but if we come back to teaching, I think an important point is, I would say, starting with research plans because most researchers are good at writing proposals and research plans. They know that and then say, okay, if you write a data management plan, we use a different structure, different things go into it. These are the differences and that seems to help. Thank you. Thank you very much. You also covered a lot of things. And thank you. Yes. Definitely. It should be like from a technical point of view should be a tool that connects and supports the administration. Because there are so many different steps for researchers to take and to manage the data, different committees and ethical committee, for example, that they have to consult data access, maybe committee. And, yeah, different, different people inside the organization. So that's something that we support. And this is actually, yeah, this, this, this we support and you will, we can, we can show an example of how we do that later this year in the new release. So what you said, Teresa, for the, the local to that you can add your information in one, two, and then have two different types of reports that's also something that for sure suppose so we need to make sure that we, we help researchers also in that, in that matter. And yes, in terms of the training. So, examples of how they can better their work basically their efforts. Okay. Thank you. Thank you so much. Anyone else that would like to contribute to the conversation. For example, I reviled them. Since there is also mentioned integrations with administrative administrative life lifecycle, let's say. Maybe that's something that looks familiar, similar to your case. We cannot hear you, you're muted. Yes, to be honest with you all. I'm here trying to find a way. I always worked as I said before, I always worked with data infrastructure. And I know that, for, for instance, one of the goals of the oldest project like open hair and so on. They use or they manage the data to be stored in any place I don't I don't care about this. And I'd like to, let's say, use my understanding in data infrastructure to, let's say, to find a way to be more productive to more to be more secure, and so on. And I try to understand what this data management plans need to do. Of course, I understand that they, they will not the main reasons to have this is to have a common way to, to exchange information between researchers and so on. And I'm trying, I'm here trying to find, is there a way for to use my understand infrastructure to be more productive in ways to, because today, what you see today in terms of data management in general is that every day there seems to be a new way to to store data. And, of course, and we are seeing all the time, data growing and growing and growing. And there has to be a way to understand that, let's say, in five years or 10 years, maybe we will have another way to store data. In the future, or at least for some period of time, I don't know. Is there a way to use our understanding how to manage data to be ready for the future. Yeah, I don't know if he, I see you. I'm here to do I try to understand the way you do things to maybe to help you see what you're not doing the future. That's my main reason to be here. I see. So you see DMPs as the tools and the let's say yes as the tools that will show you where, like the storage capacity, like how it grows and evolves maybe and where where like the services that are used the size of the data so you're more interested in on the, let's say, tracking of the storage through monitoring the DMPs evolution, let's say. So you want to know, yes, in the section for example DMPs talks about costs talks about a size of data where they are stored the service, so you're more interested in that. I now understand the case. Yes, you can. Yeah, for sure. But that I'm trying to understand this environment, you know, I'm trying to understand this environment to see if the knowledge that I have today can help in the future of in terms of my feeling, open access, open data, open science is everything that I think that is really the need for the future for the humanity. And I'm not saying thinking about only about me or about some institution. I think that is very important for the humanity. Definitely. Thank you. I think though that your, your approach is more on the exploitation of the DMPs than of the creation of the DMPs which they relate though they relate, because for example in Argos or the software, you can have a section where it is about storage, and you can add as many questions as you want make it as specific or as minimum and minimal as you want. And connected to the storage capacity of the university, for example, so that you know, at the beginning of the research activity, what they will need the researchers will need, because they will have added like I don't know five terabytes. This is very extreme example. And then at the beginning you see the actual consumption and what they did, I mean what they used, you compare and then, yeah, then you exploit basically you do your own analytics and yeah. Okay, I see, I see. Okay, thank you. And you are Kim. Yes, I think it was very interesting. Well, this perspective here because you're actually touching upon some of the possible incentives for the from the researcher perspective to make infrastructure and DMPs as part of the infrastructure into something that ceases to be hindrance to doing research but actually is perceived as a benefit. This, these tools help me keep track of my own research and access other research data and research outputs that could be be usable for me as a researcher. So, so I see both these measures of access and security and ordering of your of all your data because the many researchers today have their data spread out and their outputs spread out on private hard disks and cloud servers and whatnot. And not having actually complete overview of what they have so if DMPs could actually, I mean, serve these purposes to make life easier for researchers, then they could, I mean, then I think they would, there would be more incentive to also to share DMPs and publish them and make them part of the knowledge graph so so so I think you're on to something important here. I also see Alan has a comment I think he writes, I think the main challenges around DMPs are more social, political than technical. We can design very smart tools. It will not help much if people are not interested in using them. Yes, researchers are understandably not super excited by DMPs whether they are word processing documents or online questionnaires. In a past log data weeks, we have produced short movies with horror stories about loss of data, missed deadlines, etc. That was quite fun actually but I think it would be much better if we could show success stories. Yes, researcher testimonies where they could explain where the DMP has been useful for them in terms of time, energy, I'd rather avoid the topic of money to close to the ground application situation. Yes. So success stories. That's also yes, I think I think that's also something that we need to You don't have a success story though yourself. Okay. We can find success stories. I'm pretty sure that we have many not for the whole DMP but you know for a specific area that the DMP tackles and we can build on that. Yeah, but I really like your your comment, your right. So since you. Okay, by Zaha and Paula, thank you for joining. But yes, in terms of since you mentioned political influence let's say and how things don't play well for DMPs. One thing that was mentioned yesterday in the session was the lack of understanding researchers their lack of understanding what kind of details should go into the DMP. They don't know. They might know where to start, which is what Teresa mentioned, but they don't know where to stop. So that's, that's something that was mentioned yesterday. And the idea, the idea of the discussion was like, can funders support this can funders support the community. Present what what level of detail they search. How they evaluate the DMP is because this is close. This is a very close to the activity. It's not open. So the DMPs are evaluated and what is perceived a good DMP, which may may may be also is what you were saying Alan with the success stories. But who is the person to say that this is a good DMP isn't the funders and institutions that have the policies. Open discussion. Who wants to take, take the mic. Maybe I can start because I, okay. I see. Sorry, I saw your hand. Yes. Thank you. That is difficult. Because we do not have. We do not have evaluation criteria for data management. I think we can give advice to researchers if you see that there are some things that obviously are not going to work. But as we so far do not have many success stories. I think we were desperately looking for researchers who were, who were willing to share their good experiences from writing data management and so forth. We haven't found them. Which does not mean that they don't exist, but they do not. They do not seem to be in our near environment. Let's put it like this. Yeah. So, at the moment it comes down to formal aspects. So basically administration of all legal requirements fulfilled are the formal policies of a funder fulfilled if it comes to data management plan. We can try to share things that did not work for us when we worked with research and where data management plan possibly could help. But we do not really have examples. So, thanks to having a data management plan, this project went much more smoothly than it otherwise would have been the case. So, yeah. If it comes now to our situation in Sweden, we have some major funders who require data management plans, but they don't want to see them. So that's up to the universities and the departments to make sure that data management plans are there. Yeah, that makes it also difficult to make progress. So sorry, and a real success story yet. We very much would like to have one. And I think that links a bit back to what I said earlier. Perhaps we can come closer to success stories if researchers see that writing a data management plan reduces the burden of administration. That might be a way that works perhaps. Thank you. Thank you very much. And I see Joachim has a hand up. Yes, connecting to what Teresa just said. So, since the funders are not interested in seeing the DMPs and evaluate them in any way. So, this task is now in principle in Sweden on the head of departments, shoulders, and they don't have time or to really assume this. But in our local template at Stockholm University, we have a checkbox that the researcher is supposed to fill in to stating that the head of department has seen my DMP and approved it as fulfilling the requirements from the funder. So that's one way. And we also have developed a schema Tron validation schema, which it tries to evaluate the DMP on not the DMP actually but the full what the statements in the DMP would entail in terms of complying with the fair principles. So, given that they fulfill everything that they say they will in the DMP, they will get a certain fair score on all the FAI and R levels. But we have not as yet. I mean that the plan was to to communicate this evaluation back to the research is for for feedback, but we have not done that yet since we have to we are still developing this tool but and also I mean, as as the developer of it, I tend to think that who am I to do this evaluation. When it actually is not on our, it's not our task to do it, but the only reason I would do it, it would be to, if I knew that it could be of help to the to the researchers themselves so but but we're still thinking about that. Okay, interesting. Yes. And I see a land has books. Okay, has another comment. Transparency wasn't the right word to use. I don't mean the various actors are keeping the process obscure on purpose but the information that can probably be shared certainly doesn't circulate as efficiently as it could. That's true. This makes it difficult for everybody researchers support teams funders institutions to learn from each other. Yes. And since you mentioned in your game since you mentioned the fair compliance. This is also again, what does it mean like they ask about fair fair like apply for principles but how we can support the how we can support the when do we know that this is we reached the compliance, we don't know. I mean as researchers and this will provide some we don't know. So this is something that for sure I agree that we should pay attention to, let's say in the future. And actually, in the context of the new project that I mentioned we're going to get the input from different funders across Europe. See if they can help us understand what they want, so that we can, you know, dry a line and say okay, this is the minimum that you do and this is the nice to have. Maybe, let's see. Sorry, must leave yes by by Johnny. Nice to have you here. Yeah, and I see that we're actually, and it's, it's three Central European time. So we should be wrapping up. I don't know if you have any last points that you would like to be heard. Okay, then. Thank you very much. And you will see each other in the month from now. And we'll have many things to share in terms of new developments that some of you wanted. So, yeah, we'll go back to the Argos and open DMP focus let's say discussion and demo next month. So, thank you very much. I really enjoyed this discussion. Hope we had more time, but let's see maybe in the future we can, we can, we have new opportunities. Bye bye. Thanks for joining everyone. Goodbye.