 Perfect, then if you can go to menti.com and enter the code 515030915, maybe I can also add it in the chat. Good, let us know where are you connected from today. For example, I am connected from Greece, although I was supposed to be in a different part of the world at the moment for a conference. But today I'm connected from Greece. Good, we have Greece, Switzerland, Cambridge, UK, Budapest, Hungary, Italy, Spain. Yeah, Sweden, everyone underneath new people are joining but hi to everyone. Good to see you here. All right. Next question, and this is the last question that I'm going to ask, you know, about you, which domain or is this community you belong to. So let's say I'm a librarian so I am under where is it, where is it. I would consider myself engineering and technology, more social sciences. So lots of social science participants engineering technology, natural sciences, medical humanities and all. And please feel free to, as we are moving on to the discussion to, you know, turn on your camera, turn on your microphone. And again, this is more questions, you know, post questions that you have to this discussion. These were some questions that I added here just to help facilitate our interactions, but feel free to, you know, this is for all of us to interact, right. So, you know, a lot of discussion happens around data months and plans, and in Horizon Europe, we see that not only the data sets should be documented but also the part of the code like you know the software and other research outputs this is mentioned as a term in the template and the guidelines so it comes to, to, and to me, it gets confusing, let's say, to me, to the outside to someone that reads all those patterns right gets confusing, can be confusing what is a DMP at the end. But do we consider a good, oh, sorry. This is another question. What do we consider a DMP. And what do we consider a good practice for a DMP. So, what is a good practice for a DMP for you. For me, for example, is being able to provide this information either that that is requested on the template or not. And if I give it to someone they can understand exactly what I did know what I used, they can reproduce my, you know, if they follow my workflow so if they use my data, they can reproduce research that I did. So what is it a good practice for a DMP for you, for example. Yes, I would, I would say something similar to you. If you can identify, yes, if you can tell us. Sorry. Yes, I'm for this I work as part of the chemical engineering here at National Technical University of Athens, I support research lab essentially with you funded projects and therefore I have to engage a lot with data management plans. And it is a very confusing document for some in some ways that you have to produce at the end of the beginning of the project. There are a lot of things I could talk about the MPs all day long, but to answer your question I would say it's an it's an transparent accounting of what happens to data throughout from beginning to end from production to how you are going to manage them with the, you know, some of the questions that are part of the, of the template which is usually backup storage security, if you have sensitive data. If you have confidential data, if you want to keep them closed or open so you have to define a lot of things within that document and I keep going back to the word transparency so can you see exactly what, even if your data is closed. Exactly what is the process that was followed to make the data closed and what does it mean closed is it's still accessible somewhere, because that's, that's, that's a big question as well. So, but it varies when you say DMP it's a project of that lasts for years it changes throughout the year so I think that would be my answer for now but there are a lot of elements I think that we could be talking about within the DMP and how to approach them. Thank you. Yes. Thank you, thank you for this yes transparency, I think is what should drive the writing of data management plans and the recent data management activities overall. Pretty sure others agree as well. Anyone else who would like to take the mic. Hi, yeah. This is from Italy. I am a research project manager, and mostly deal with, let's say, biomedical engineer project. Thank you for the project and I mean, one thing that would be really great to have. Well beside the standardized template, but also information on the level of granularity we have to reach those documents, which are really preliminary and so you never know how far you should be. There are some KPIs, which also like self assessment KPIs, like a text box page where you can say okay, this is that this is done and this is done as the correct level of granularity. Yes, so by KPIs you mean something that you can feel that you're on the good on the right path, moving to towards evaluation at the end of the project right. I mean, some key performance indicators, which could be either qualitative or quantitative but sort of sort of self check of what you need to achieve and how far you've reached to. Yeah, yeah, that's also very important. Yes, and the granularity I think it's, it's again, it's also a challenge that can make the writing of the MPs really hurdle. So yeah, the KPIs could help facilitate this. Thank you Anna. Thank you for sharing this. You're welcome. Anyone else. We heard transparency we heard granularity. I see someone has raised a hand. Julia. Yes. I was a researcher a few times ago about medical science and when I was working with industry in the pharmaceutical industry. The DMP was not called the DMP, but it was still part of the request of the regular theory agency in order to perform the clinical studies. So every time we had to think about the size of the data that we would like to have. And I think that the DMP is, let's say training at some point at the early career researchers, but also the researchers to go into practice that cannot translate the experimental research into something that can be even commercial at a certain point or can be useful for contextualize the research in other field. Sometimes we don't think about the ethics or the commitment that we need to provide as information and having in that directly in a template can be very useful for thinking about at least. I like the what you brought here the training this aspect that's in order to have a good DMP you say that you also should be trained accordingly right to the resist data management. Life cycle. Yeah, thank you for sharing this to you. Anyone else. Let's move on then to the next. And then we have a question or, you know, issue to to trick our minds a bit. What does it good and complete DMP look like to you. Similar to the previous, but, and I think the granularity part can also be can also come here to this question as well. But, so you write a DMP. How. When do you feel good about it and you feel that you've completed it. So if, for example, I'm writing it for a horizon project. I feel complete, like when I have answered all the questions that say that are requested. And yeah, this is my my answer for this. Hi again, I don't think I'm able to always answer all the questions, because, again, when you have to submit a deliverable like a DMP in month six, it cannot ever feel complete. So there's a problem in this process with with Horizon Europe because when they requested DMP, whether it's a draft or the final version, I think there are stages and each stage looks different. So, if I had to answer in the first six months, my priority for example was to get a good account of how many data sets and what kind of data we're going to produce. I couldn't go answer fully the fair questions so it's impossible to do that before you have the data. So, it's a balancing act, I would say in the first stage, and I'm not able to answer about, you know, what happens later in the project because I haven't done that yet. But I think, yeah, to some degree, answering all the questions as effectively as possible, would be a good, good answer, I guess. Thank you. Yes. Thank you for this, I think you're right there are different stages and different things that are requested at the same, but I see another hand from Joachim Phillipson. Joachim. Yes. You want to identify yourself. Yes. Yeah. Oh. So, I'm Joachim Phillipson from Stockholm University. I'm not an active researcher right now. I was, I did my PhD a long time ago, but I work as a research data manager so I'm biased by that fact. I would agree with Fotis and others who talked to the previous question of all those necessary features about transparency, for example, and I would say that a requirement for, and I would also say that agree with Fotis that DMP is a living document that is updated during the whole research cycle. So, so you cannot say that it's complete until the project ends. Really. And at Stockholm University we have made our own DMP template, which we like to believe supports these, these necessary features of transparency by being machine actionable. We have very few free text answers we have check boxes and drop down menus to fill out and we explicitly state you don't have to to make a definite choice yet and we archive that is we download the DMPs at two different stages. The first is when the head of department, that is the system in Sweden has, so to speak, supported or accepted the DMP as fulfilling the funder requirements, and the second stage. In the second time we, we download and archive the DMP is when the project is finished. And so, so I would agree with that there is no definite time when it is really finished until it's finished, so to speak, when the project ends. Thank you. Yes. Thank you so much. Sorry. It's not like Kim, as I thought it's Joachim Joachim. Thank you. Yeah, it's different layers. Yes. See two more hands. So I don't know who was first though I see that in the chat first was Alan so I'll do you want to say a few things. Yes, hello. My name is Alan Borrell. I work at the Swiss Federal Institute of Technology in Lausanne, Switzerland. I'm, I work at the library as part of the research data team. And so we read many DMPs, some, some very good some very bad, most of them in between of course. And yeah, all jokes aside, I think that the main things I could say about a good DMP are actually not related to the DMP part, really, it's a it's a living document that that grows with the project. And so, and everything else is really details that will be connected with the project with whatever research is happening and so and so every case will be different and it's very difficult to say what is good or bad. I want to perhaps take one step back and just take the broad framework and I would say that a good and complete DMP at one point if the project must be consistent with the state of the project and also with the description of the project. So it must be realistic in that it really represents the understanding of the project at that point, and every information given in the plan must be at least have some level of, of consistency, there should be no contradiction, no internal contradiction. And it's often very difficult to say whether that is the case because we don't always know more about the project than the DMP itself. So that's an interesting challenge. Yeah, thanks so much. Of course, yes. There is that there are the templates let's say and what they require us to add or what they suggest or encourages to add this information but at the end, those that are working in the projects know how the DMP should look like and when it is complete. So, according to, again, as you mentioned the project objectives and the disciplinary aspects also things. Thank you. Thank you. Anna. Yeah, see me. No, I mean, maybe it's a bit redundant what was already said before but to summarize a bit to me a complete DMP is the one who which summarizes the whole life of the data in a project so from the data collection processes and all that goes with it. The current processing and use of the data in the project and what happens to the data after the project. So the past president future I would say that's what I was surprised at this concept. Yeah. Thank you. Thank you, Anna. Yes. So, basically, all the steps of resist data management lifecycle. Yes. Okay, I see no hands. We'll move on to the next. How clear is the DMP definition for you and this is what I was telling you at the beginning that now DMPs are about software about protocols about other research products what are the others is products and how do we add them in this DMP you know how how clear it is for you. If you go to write your DMP, all those different elements. Is it, let's say, let's let's rephrase maybe. So, do you feel more comfortable. We have a hand. Let me see if I can rephrase first for this and then you can go ahead. If I have to write a DMP, do I feel more comfortable or support someone interact in the interest rate. Do I feel more comfortable in advising for data for software for others as products. What do we feel more comfortable and photos you can go ahead. Hi, hello. Hi, sorry, sorry, I didn't know how to raise my hand. Let's open the microphone. And, well, I am the data manager inside the European project, which is you apps for data. And in this project, we do cascade funding. And we found the experiments that must involve SMEs. So small companies. And all experiments are on the use of data are based on the data driven. So what I asked for each experiment and we have a three open course. Now it's going on the second one. We had the 10 experiments in the first one 14 in this one. And then there will be another another call soon. And I asked to each experiment is to produce a DMP for the experiment. But in this and I recommended that we use this platform. Okay. What do they find the difficult in the DMP definition. So we are only talking about the data set we're not talking about software. What they find difficult is that the questions that they have to answer are a little biased towards the generated data sets. So, but they are asked also to to document to describe the input data that they use, because it's mandatory from the European Commission to describe all data that are processed in a project. So when when they have to describe the input data, the data that they collect from other external data providers. They have to declare a lot of things like the usage of metadata, the license, how long they are preferred and so on, which are information that belong to the source to the data source. They may even know what to write. And I don't know what to advise them because I, I do think it's a little biased towards documenting and describing the output to the generated data set. Yes. So, what project is this and I cannot, I'm sorry, so I cannot. Is it Horizon 2020 or? Yes, yes, yes, yes. 2020. Yes, yes. So, you don't have to document in the data management plan. Yeah, you can document the experiments but there is a data management plan also for the project itself, the UAPS for data project, but since we don't really have any control over that we don't have a repository for the project, we don't have data ourselves. So it's just, it's just how we use the information. Our partners and so on. The open calls you mentioned. Yes, the open calls and the experiments are the real one that use the data set and produce data set. Yes. So, so the horizon 2020 template can be used for both the outputs. Yes, maybe not that much. Because the mandate is on the research data that you have used in when writing a paper so both of that, you know, validate your findings on paper. Maybe you're right that they're, that they are a little bit biased. What I would suggest is that you contact like, like, I don't know, contact Argos at the point that you and we can have a template that fits your needs so that you can use it for the open calls. That's also possible. Because it's outside. I understand that there's something different and activity that you want to document the data. Yes, so we can do that. We can do that for sure. We should I contact me or Argos at the point that you get Argos at the point that you and I can, I can take it up from there. Okay, thank you. Thank you. Let's see. I think it says it is defined by the DMP template we base our machine action local template on the general sense Europe model. Yes, so this is about the definition yes, and Julia Caldoni says I support research groups financed by Horizon Europe program and the most difficult thing to define up to now are the other research outputs yes I don't know if you want to say a few things Julia I can say a few things about this, but I can totally relate with you. Hi, hi, hello. Yeah, I'm a that is to word actually and I'm just starting my support. So I've seen like just a couple of DMPs up to now but one of the most difficult things has been to invite the researchers to reflect on what these other research outputs could be. Because many times I think that they actually already know that they have these outputs that they don't have only digital outputs. I'm a biologist so I think about like cell lines or samples biological samples. And so I found difficult to help them balance how they should improve new methods to implement fair management of these outputs. And how to tell them okay you're already doing this you're already like naming the samples you're like versioning the samples. So maybe you don't have to invent anything new, you just have to describe what you do because that's already kind of fair. And that's the most difficult thing because now we don't really know what Europe would like to see written in DMPs in this section so we're kind of trying to to understand. So I don't know if anybody has experience in this in this paragraph because actually it's just a paragraph. It's really really challenging. So thank you. Thank you Julia but I think that you approach it the right way like take the principles and see what it's already like how the different outputs like the others whatever this means apply them. It's also difficult to understand what that means what it means because if you have software, it's like okay that's simple to understand, but when we have like prototypes or right cell lines or stuff like that. It's difficult for me to understand and to help them understand that that's also an output of their research. But yeah, we're trying. Yes, that that's can I can I offer my sympathy to this to this comment because one of the projects I'm involved with. They do have a lot of prototypes to produce and I'm not sure if other research outputs means actual actually talking about the samples they're producing the experiments they do on physical material. I don't know if it can be that I wrote for month six I didn't include that in my definition there, because I'm not sure how to manage the, how do you. The end, I mean they will produce something from recycling processes so they will at the end come up with a solution to do better recycling and recyclables and recyclates that's the definitions I'm working with. And if I'm if I should put information about that kind of printing that they will because I think most of the prototype will happen through printing or some other means. So I don't see how I can follow through on that, if that makes sense. I think that definitely makes sense and I actually came up with this definition because I'm working with a project that has product I produced to, and I told them that they should describe what it's useful to reproduce their research. So not the final prototype, but maybe if they have like midterm version, putting up together like experiments or pieces from different parts of the research and like documenting that because of course they would tell, they would talk about this products in their publications probably. So they will have a reference they will be referenced somewhere so they just need to make clear that these things exist so maybe photographing them could be a documentation of this thing. But yeah I actually didn't tell them to do this things on the final product but on the on the parts that could be useful for someone else to maybe reproduce the prototype in 10 years from now. I don't know if that makes sense. My, my, my comment is, what I wanted to add was that I'm not sure if I can use that to make it open access for example fairies, you know to make it findable accessible I don't understand how you make that kind of product at the end which is other research outputs, discoverable through fair means, and what is the point of that and a lot of this information will be included in other deliverables so when we talk about data management I'm not sure why. But what I categorize as data does not fall with that kind of further definition samples maybe yes because you do have data that associated that is associated with samples that you get for example from from a lab. For example, I had to work with something that that they took blood samples. So there is data associated with with the samples and you had to make them anonymized and all of these things so it makes sense for me to mention that but even when I had this discussions with researchers they were mentioning that this is all mentioned in the ethics part why do we need to repeat that in the data management plan and I, I sort of see the point. So we need to. I think they either need a broader definition of what is a data management plan or not calling data management or. Something else. Yeah, I think I would have. I've thought about it a couple of times why they why the D there now that everything else is needed to be documented. So, yeah, maybe, maybe we can call something else. Maybe we include more parts so like the ethics the data access already existed so other parts that are useful for management. I personally approach it from the horizon 2020 perspective where you focus on the publications first. And that's my my guide as it were so I focus on what kind of data can be reproduced essentially because if something cannot be reproduced if something is very unique or it's just a unique experiment that there's no point maybe you can publish the methodology you can show that what you do as a lab or the work that you do in some way without revealing a lot of intellectual property that you own, and I think that that's my focus on the data management. I can't share everything the way they are asking you to do it. I think it's impossible to manage that because it's most projects have more than 15 partners how I think it's impossible to put that in a framework if you know what I mean. Yes, well that's why the Monday is the mandate is only for the data of the publications right the underlying data. In horizon 2020 horizon Europe is not very specific is horizon Europe is not specific with that respect and that's where the confusion comes with other research outputs. And that's why I'm focusing at the moment until I hear otherwise on software coding and simulations on other research outputs which is something I can actually define and and make open because the the actual outcome the physical products I don't see how they fit in this. Yes. If I can I would like to thank for this for this insight because it was really helpful for me. As I said I'm just starting the support so I, I couldn't see that clear right how to manage this paragraph and this part of the dmp so thank you very much because it would be really interesting for part of reflection from my side thank you. Nice. Thank you thank you both Julian for this. So now we'll move on to the next question which is, well, it was mentioned hidden maybe in this. And Julia's actually answer. How clear is the third definition for you. And I think if we tie the fair to the others as outputs we've already said it's difficult to understand. But do we feel like after completing a dmp. So are we confident that our data and software and everything is fair. Do we miss like, how do you feel about it. I understand there's a difficulty in approaching fair in different disciplines as already mentioned by Julia. And I see hands. Let me see, let me see, let's go I don't know who was first let's go with Alan. I think 40s was first, but I will be sorry. That's okay that's okay that's okay and go ahead go ahead. All right, thank you. So, yeah, I think the dmp usually make at least a reasonable job of addressing f a and I. For the are reproducible pot. It seems to be that it's often difficult to tell from the dmp whether the data can actually be reproduced. Findable. Okay, you need to propose some solutions for that accessible interoperable as well. The reproducible pot, I think is often not really there. Just to say that for the fair, it's not reproducible. It's reusable reusable. Oh, sorry. Okay. Yeah, right. Okay, so how clear is the fair definition for you. Okay, 75% I would say. Now I agree usability is still often a weak point from from my experience. I think we've had this conversation before about interoperability is a challenge. What I want to say is I know I think in some degree how to make everything fair. So for example, if, as I said earlier, if if there is an experiment in this lab. And if I if I document the protocol the methodology the numbers the conditions the measurement the experiment that the model of the instrument that is used everything and if I make it possible that everyone can search for something find it access it through licensing or repository. Then that makes it reusable. Even if it's, you know, let's say in the best possible conditions you make that open. I think that's okay. I think that the biggest challenge is the interoperability of machinery double actionable things like data moving across systems and platforms which this is not clear to me yet. We've had this conversation before about how challenging this can be. But I think to some extent for verification can be achieved even with not having a full interoperability, let's say, completion rate. But to some extent if you provide enough documentation to make up the context and to that the conditions that you need to reproduce an experiment. And to give them exactly the data that you have, as long as there is the process, some were documented, then transparently as I said in the beginning, then I think that's that's as fair as it can be if you like. Okay, so what I'm hearing from both of you and from others actually since the beginning is that, apart from fair. I have like, well, not maybe apart from fair, but reproducibility is key. And it's what drives actually the documentation of practices of instruments of models of all the different outputs and elements in your research. It's fair understanding how fair can be applied. So, Anna. Yeah, so one other thing. Let's more effort is also be made on the concept of data model. Let's say that the standard like almost fire and all that regards the definition of a common data model for the project and possibly taking into account existing data models. I think it is still underestimated as an aspect 40 MP. So sorry, please. You mean at the level of the project, not even the discipline. Yeah, yeah, I mean, because it's not stressed at least as far as I remember so this is data modeling is an activity that we usually do in projects but it's not stressed so much in the MP and I think this should be at least a high level like standard you use and Yes, how does that slide. Yes, actually there is this data alliance is working on this with the the DMP common standard and you know the different properties that they introduce. So maybe what I'm hearing at least is to translate this into a template and provide a common framework, let's say for templates around this, not only here. Okay, so the time is running so let me see I have more questions, but let's see which ones to answer. What are the most difficult out of research things that you wish you shouldn't deal with in your data money in the data management plans so what is one or two things that are requested or encouraged to have in data management plans but it's out of your understanding of, you know, what you can support so you have to turn to others to support when what are the others that you turn to but this is fine it's it's a I like the data management therapy. Maybe we can call the community calls like this. Okay. I really like the discussion the chat. Can you do you want to to share your views on that question, especially there are a lot of, we are a lot of people here that support other researchers. So, yeah, if I may, I don't know how to raise your hand. I mean either. Yeah, I have to agree with the guys talking in the chat because people it's really difficult to deal with. Mostly we have to write a dmp or support the writing of the dmp forum. A group of people a group of researchers like partner partner, I don't know how to say it in English. So partnerships thanks to my colleague. And so that's very difficult because you have to explain these things, all the things that you have to put in the data management plan to the researchers you are dealing with in your institution and in my case, and then they have to report all the things to their partners and often they are probably they already know everything. They actually don't know and don't want to hear so you don't have this one to one in my case I don't have this one to one interaction with them. So it's very difficult to make them understand why they should do that because it's not just like you have to do it because Europe is asking you but it's actually because it will benefit you. And if they don't want to listen that's there's no way to make them listen so yeah I really have to agree with the guys and. Yeah, sorry, that was my five cents on the question. Thank you so the human aspect. Yeah. Thank you. I don't know if anyone has anything else to say. Maybe let's see. Another question. Maybe let's move. Position ourselves in the future. And think of what we want and how we wish things in an ideal world today around data management plans and how does the future look like to you. How do you think this can help you. Sorry, can I just offer my to give my thoughts on this. The phrasing of the question I don't know. I don't think the MPs can help us in any way. If I had my thought when I read this question is what I would love in the future would be to actually speak to someone from the people who evaluate the MPs and look at what they think is a good practice because at the moment I think it's between the it's within the communities that we think oh, this is, this is a good idea. This is yeah you're doing it the right way we're doing it in another direction and in order to get consistency and simplicity with these things, not for the sake of simplicity I mean it's already complicated to do what they're asking us to do. But I think it's important to be able to get some project officers that they review these things and just get their thoughts on different DMPs and say, you know, you know these elements are good these elements are bad, because we received some comments on the DMP and it said it talked about exploitable results and to clarify the position on exploitable results and I'm thinking there's not a single word on exploitable results on the DMP templates. So from from the EU so I don't see where this comment is coming from I don't I couldn't link it to something that was written in the DMP. Personally, that there are some practices within EU funded projects that are odd in terms of how they manage a data management platforms and what they consider the management it's a little bit contrary to what I understand it to be where my focus is more paper review paper, you know, driven. So these are the things that I think in the future. I would love to say would love to have a meeting with a few project officers and say you know this is the direction we want you to take and just get a take on it not just comments on different because there needs to be consistency. What is a good DMP on what is a DMP. I really agree so in the context of the ESC association task force for fair metrics and data quality. There has been a white paper I think it's out already, but we worked on that, not me, but the other members of the task force on providing the guide guidelines. So the discussion would say for a data for a fair assessment body governance body to be established so that it's easier to understand what fair means in different disciplines. What does it mean for different, for the different things to be fair and to, to be fair compliant, either when creating software or when describing the world where when reusing or generating data and so on. So, I see your comment more towards the this fair, like the governance part. So, yes, thank you. Exactly. So it's something that we really hope yeah thank you. Okay and we have four minutes so I will skip to the fun part. The trivia time. Let's see how well you know Argos now talked about the MPs talked about the future and puzzle ourselves. Let's let's see. And the winner will have the possibility to create one template of their own in Argos guided by our team, right. Please. Okay. When you're ready. But this is timed. So you have to be quick. There will be five questions. Not only one answer will be correct so there may be multiple answers that are correct from the list of the provided answers. So with that. Five, four, three, two, one, go. They give me more time. I can use Argos to describe data sets software my life policies be quick. Good data sets and software is the correct answer but it's good. Maybe you didn't know that so now you know something right. You didn't give me the option to press both data sets and software which I would have done once I click data sets once I click data sets it didn't give me the opportunity to answer something else. It's okay then maybe I didn't test it correctly sorry, then maybe well that it's then up to the fastest only not to the most complete answer. Okay, next. After I finalize my DMP in Argos I can go drink a coffee or beer, according to preferences and time. Publish it and get DIY, leave it there and pray it did its job and do finalization to fix at something that I forgot. Good, good. Publish it and get DIY and also, and to finalization and fix whatever I've got. Next, to work with others in Argos I can invite them on the whole DMP, call them on Skype, tag them on Twitter, invite them on the data sets I want them to contribute. Yep, invite them on the whole DMP and on particular data sets. Next, so it's one. What automation did Argos introduce at the beginning of the year. So this gets tricky this one and the next questions are tricky. APIs, pre-fill, exports, or the notification. Yes. Yes, so in January or February we introduced the pre-filling of DMPs with information that are coming from other sources basically the model. And we're now exploring to expand this. Good. Five of you already knew that I'm impressed. And the last. What is the next feature that is released by the end of the year. We told, we talked about this in the previous community goal. So is it new exports for DMPs, machine actionable table tool is in described data sets, more repositories to publish DMPs or more pre-filling options. One of those things is going to be released soon. Yes, so it's machine actionable table tool is in described data sets. I'm really impressed. So those five people, I don't know if you are the same than with the previous question, but well, well done. Because it was the trickiest. And let's see who was first. Whoo. Okay. So Julia was the fastest. Congrats, Julia. We can now work together like, you know, have a meeting and work together to create your own template in Argos. That would be really interesting because we, we're really looking forward to do that. So I couldn't imagine winning, but yeah, okay. See, you never know. Thank you. Good. Well, congrats to everyone else. You know, except Bianca, I don't know if they're the correct names. But yeah, congrats to everyone. Thank you for, for, for taking this quiz. Stop sharing because we are, I think we are over time. Yes. Well, thank you very much, everyone. That was really nice to talk about all of those things with all of you. And I like that you also had to, to say a few things, you know, exchange experiences and practice with each other. Always a plus and this is why we're doing this community calls, not only about Argos but for, for, you know, to be better, to be able to better support research and researchers. And with that, I don't know if you want to add anything, but I would wish you a nice rest of the international open access week. And I will, we will resume for next month, right? Yeah, next month for the last community call of the year, I think it is. Thank you. Bye. Thank you, everyone. Bye. Thank you. Bye bye. Thank you.