 Okay, so let's start with the introduction that more people can join, so welcome to this last session, in fact last session of the OpenAir Week 2020. It was a great week with several sessions, lots of excellent presentations and speakers. Including open science gateways to open and link in research outcomes is the topic of this session where we are going to present the OpenAir Connect related services that are supporting the services that OpenAir have to support research communities and research infrastructures. So, just before we start with the topic and with the presentations of the speakers and just housekeeping. All participants are muted and cannot show video but so you have the possibility to ask questions in the Q&A. I will answer all questions directly using our audio from the speakers or in the chat, all the presentations and recordings will be available later today in the OpenAir Week website and the recordings also will be linked from this web page also available in our YouTube channel. Please use the hashtag OpenAir Week 2020 to share your thoughts in the different social media channels specifically in Twitter. So, this session on the OpenScience gateways, the services that we are offering to research communities and research infrastructures, we'll have three main blocks. Okay, we will start with Alessia Bardi from that is the manager, the product manager of OpenAir Connect to present the relation between the services that we are providing to research communities and research infrastructures with the OpenAir Research Graph. An example of one of the latest gateways that we have developed, the OpenAir COVID-19 OpenScience gateway and then we will stop for two, three minutes to receive questions. So, we will try to have a more interactive session not to have all presentations because we have several speakers. It's a more risky way to manage the session but let's do our best. Then we will have five use cases, so real OpenScience, six, sorry, six use cases, so real gateways that we have in action to present to you. And after these use cases, we will have also time for questions and answers and then we will finish with Alessia again and with my colleague Eri from the Tina Research Center to present some of the recent OpenAir collaborations projects that are also benefitting from this service. Alessia, the floor is yours to present the OpenAir Research Graph in the connection with the service. You can share your screen. Be aware that you can put your questions, can share your comments in the chat and you can put your questions during Alessia's first presentations from Alessia and then we will reply to your questions just at the end of the second presentation for Alessia. And welcome all. Okay, so I think you can see my screen now. Perfect. So with the other speakers, you can close your camera and just to have. So the OpenAir Research Graph or how I learned to stop worrying and use connect services. So why we should be worried, because researchers have many questions, especially in relation to OpenScience and all the different aspects of OpenScience and on scholarly communication in general. So it is often very difficult to find, for example, the research activities of a specific discipline because the research products, the research results, the publications, data sets, software, and all other types of research products that are produced by researchers are scattered. A scattered across many different repositories, archives, data centers, and it's not easy to find out where to go to find them. And also, if I'm a researcher using a research infrastructure, a digital infrastructure, where can I find the results that have been produced thanks to services that my research infrastructure offers. To its researchers. How can I know if others are using this digital service to analyze this kind of data, for example. And then we have the questions of researchers for OpenScience publishing tools. So first of all, what does it mean to publish according to OpenScience principles. So what should I do to follow them and to make my research more open and more reachable and reusable by other researchers. And are there any best practices for my research communities in my own domain. These are questions that are not very easy to answer. But if we look at this from the point of view of the research infrastructure or research initiatives, for example, I don't want to know who's using my services, my infrastructure, and I want maybe to use this number in order to present some to my current and future funders to say, you know, my services are used by many researchers and thanks to my services, they produced these innovative research results. So, and this is why we work on the connect services. And here today, you will hear this word connect a lot of times, because it's all about connecting things with each other. We connect research entities, because we will see how we can add context to research results, because a publication is just the tip of the iceberg. There are data software, and there are semantic links between these things. We connect researchers to open science. So we empower communities with open science publishing tools in such a way that it's easy for them to apply open science publishing principles to their daily work. And then we connect the research infrastructures and research initiatives to the scholarly communication lifecycle. Because the current situation is that the place where the research is performed, which are the research infrastructures and the place where research is published, which is the scholarly communication word ecosystem, they are separated, but we want to make them linked. So we want to reach this gap. How we do this, we do this by building open science gateways open research gateways for for the communities. And these are built on top of the open air graph. What is the open air graph. It's an open metadata research graph of interlinked scientific products with access rights information with links to funders and grants and research communities. And when we talk about a graph, we talk about a model for representing the world. And in our case, the world is the scholarly communication domain. So we use nodes of the graph to represent objects that can be linked with each other with relationships with semantics. You can think of the semantics as the reason why these objects are related to each other. So for example, a publication has been funded by a project, and the project has been funded by a funder, for example. How do we build the open air research graph. We collect metadata records from more than 70 K data sources from all over the world. So not only Europe, but also Asia, Africa and South America and North America. And here in this slide you can see some numbers so for more than 400 millions records collected them links, and then also the full text. And these are the full text of open access publications on which we apply full text mining technique in order to extract additional information that is not explicit in the in the metadata records of the of these resources. As you can see, we have many different types of sources, starting from entity registries like open door with the data read I see, then we have the projects from the funders. So one is Cordis for the European projects, but we also have national funders like Portuguese funders or the Austrian or Swiss Italian ministry and so on. We include the whole crossref. We include the whole the do I a J story is the directory of open access journals. We have connection with plus with with shallow, which is an important aggregator worldwide, and, and many, many, many others. So what do we do with this massive metadata records that we collect. We collected the metadata, and then we try to find the duplicates, because different records that represent the same result of the same entity. And need to be merged into one. So we try to find the duplicates we merged into one, so that we can provide useful statistics at the end of the chain, as we will see. We collect the full text, and we apply full text mining to enrich the information we already have. We also apply other techniques that exploits the information we have in the metadata in order to infer new properties and links. So that we obtain the open air research graph, which is then analyzed for the generation of statistics, and is made available in in an index that serves our portals so open air Explorer, open air connect and our API, open air research graph, which has many, many clients, and the most important I would say is the easy participant portal. So every time you use Sigma, you also use one of the open air services that are built on top of the open air research graph. Thanks to the open air research graph, we already addressed two important barriers to the open science implementation. One is the dispersion of research products. As I said at the beginning, they are scattered across sources. But thanks to the graph we have one place where we can have them all together. Another barrier is that of the focus. So focusing on research literature is really not enough for open science, because one of the principle of open science, one of the benefit of open science is that researchers can actually be obsessed, but more importantly rewarded for all the works that all the work that they do, and it's not about, it's not just about publications. So we have a graph where we have publications, research data and software at the same level. And as you can see here, we also have another typology, another research type, which is other research products, where we are currently putting, adding the research products that cannot fit the other types. So I think about workflows, protocols, lectures, this kind of objects that cannot be considered either publications, research data or software. However, this graph is huge. We have more than 100 millions research outcomes. So how can I find those that are relevant for me? And the response is the connect services. Because they are, they enable, sorry, they enable the provision of open science gateway that are a community view of the open air research graph. So open air builds the gateway for the community, but then it's the community that grows the gateway. And we will see how in the next minutes. So the open air research graph is analyzed and some criteria are applied in order to find the products that are relevant for a specific communities. These rules are provided by gateway creators with which are who are experts in the field, experts of the community. So they can provide a list of keywords, they can provide a list of relevant projects, relevant data sources, which can be managed by the infrastructure or thematic. They can provide a list of Zenodo communities and the instructions for the open air mining team for the implementation of the algorithm. These algorithms will be run on the abstracts and on the full text of open access publication. But then automation is not enough. It's never enough. So we give the possibility to researchers that are using the gateway to manually add the research products that are missing. And they can do this via the link functionality of the gateway and that you can find also on the Explorer portal. And with that functionality, you can add one single product or you can do this in bulk, giving a list of your eyes, or by providing an orchid ID. The last criteria is the propagation, which means that we propagate information from one result to another if there is a strong relationships between the two. So if a community result is supplemented by another research product, then also the latter is added to the gateway because it will be relevant for the community as well. So what can you do with an open research gateway? You can monitor the uptake of open science publishing practices in your communities or research infrastructure. You can monitor the research impact. You can, you have, you find tools for the reporting funders. And you can also view the impact of the publications of your communities. It offers the possibility to deposit any types of research products, thanks to Zenodo and the network of open air compliant repositories. Of course, it has a single entry point to all research products of your communities. And if you miss one, you can actually link it and grow the content of the gateway. And finally, we have the APIs that you can use to build additional service on top of the open air graph and on top of the research infrastructure. So this is, let's say a carousel of the functionality I just listed. So the possibility to use statistics and to have reports of the results that you can see in the gateway. And of course, you can download the report for the publications, but you also view it from the point of view of the project. So even a project, you can download a report of its outputs in different ways. So as HTML, as CSV. And this is very useful when you have to compile a report for your founder. So if you never heard about Zenodo, please go on Zenodo.org and start using it because you will very easily get a DOI for your research product and you can publish there, basically, whatever you want, if it's of course related to research. And finally, the search functionality that I'm pretty sure that some of the use cases after this presentation will also show gives you the way to discover products that are relevant for you. So not only a simple search by keyword, but also an advanced search and the search by orchid ID. And this is, these are screen shot for the link functionality. So you basically can perform a search. And you can find different products from open-air, crossref, data site and orchid. In this case, I search for my name. So I find 12 entries in orchid so I can select which one I want to input publications. Or I can upload a CSV file of DOIs that must be added to the community. And the API. So you have the dumps of the open-air research graph and these are available also for the community. So you don't need to have the whole open-air research graph. You can download just the part of it that is interesting for you. And we have the HTTP API to perform a search. Then thanks to this another API, you can enhance services of the research infrastructure for semi-automatic deposition and have the results that are automatically published also on the gate. And of course, if there are sources, data sources, repositories of the research infrastructures that would like to contribute to the open-air research graph, they can do it by becoming compliant to our interoperability guidelines and using open-air provider. So who stopped worrying and learned to use connect services? So in the following, we'll see some use cases starting from the one from COVID-19. Then we'll go through Elixir, Greece, Daria, Digital Humanities and Cultural Heritage, InstructEric, Sustainable Development Solution Network, and Epos Italy. And after that, as Pedro was saying, we will have a carousel of projects that collaborate with open-air. So, Pedro, would you like to start with the questions or should I go with the COVID-19 game? It's better. Then we take questions. Okay. So while I speak, you can also go to COVID-19.openair.eu and have a look what's in our gateway. And so, and the gateway by itself is just one of the many activities that open-air started to help researchers in fighting against the epidemic. And basically, there are three lines of activities. So one is to support researchers to publish in a fast way the new research about COVID-19. And we did this by creating and managing with the support of experts in other community where people cannot any type of research products related to COVID-19. The other line of action is to support the discovery of existing research on coronavirus. And the third line is the collaboration with the RDA, COVID-19 fast-track working group, who basically defined guidelines in order to support the data sharing and data reuse on COVID-19 and during the COVID-19, because publishing fast, sharing fast should not mean sharing bad. So here you can see there's another communities that you can find at Sling or even easier, you can just go to the main page, to the home page of Sonado, and you will find a featured community for COVID-19, which yesterday counted 900, more than 900 results of different types. And as I said, it is managed by a mixed team of open air members and experts in the domain and the gateway. So when we started to think about this gateway, we say, okay, among the more than 100 million research outcomes that we have in the graph, how do we find the research outcomes that are related to coronavirus? Shall we have a simple search that allows us to identify these products? So, or we should go with an advanced search because we have to target specific fields, but which are the fields that are relevant, and which are the search terms that are relevant? Can we do this just with a predefined query? Or we need to be a little smarter than this? And also, especially at the February, March, there was plenty, plenty of thematic sources that were built by different communities. So how can we be updated? How can we be up to date with these thematic sources and which one we should include and are indeed relevant? So in order to address our doubts and our questions, we use the following approach. So first of all, we involved the domain experts. So we made a call for experts among researchers, librarians, research managers in order to find support because in open air, we are not working on disease. We are librarians, we are computer scientists, we are many, many things, but not medical doctors. So we ask for help. And with this support, we created a public list of data sources, which we keep updated thanks to the suggestion from the communities. And so we created a Google form where people can suggest resources. And these include both data sources that we can harvest from open air in order to have the resources in the great way, but also websites that are addressing topics in the COVID-19. So then we set up different processes to identify the research outcomes related to coronavirus. So we have a set of keywords, both free text keywords and keywords from standard classification schemes. We created a full text mining algorithm. And we analyze the open air research graph and exploit the existing relationships between publications, data sets and funding projects in order to understand which are the products that talk, let's say about the coronavirus. And then of course, we have the manual additional research outcomes thanks to the link functionality. The last point, the last part was the actually set up of the gateway, the single entry point that you can see now. So in this slide, you will see all these summarized in one single slide. So collection and mining, the additional COVID-19 sources that we found out thanks to the collaboration with the community. And then there's another COVID-19 community. The gateway that shows the part of the open air research graph that is relevant and finally the APIs. So you can see some screenshots of the community, but I really hope that you already opened the website and you're trying out yourself. So the possibility to search for any types of products. And you can learn more about the sources and the methodologies and the support and organization, the creators, the about menu. And of course, you can use the faceted search in order to to drill down your, your search, and this can be done for publications for data software and other research products. And finally, the way you can get the metadata of research products on coronavirus. So the JSON dumps that you can find on Zenodo and you will find the URL. The possibility to download the CSV files directly from the directly from the great gateway based on the search performed. And the API from which you can download the metadata records in XML or in JSON format. And you will have access to this presentation. So if you want to know more, you can follow the links that you can find that you can find here. And of course, you can contact me if you want to know more. Okay, great. Let's let's use now two or three minutes to to questions. There are already four questions but we will address three and then we move to the second second part of this session. So Camila Linlow asked this service seems very inclusive. Are you planning to have any control mechanisms in the future? Or will you trust the community to take care of what are research outputs. So control mechanisms in the way that we work with the community managers, let's say to to ensure quality control of the content. What do you want to say about that? Yes, the the gateway managers are the creators and cannot actually define all the criteria and can also reject links that are made by the user so they can decide that the product that has that has been linked is in fact not relevant for for the research communities. Yeah. So, we can you we can have more information directly in the via test if less or even my colleague Erie want to provide some more input here. But let's see about it looks like you have all the information to be able to tell researchers about new publications or projects in their field, as soon as they are available. Do you do you or someone else have such a service? That's the graph have a power have lots of powers but this is a community effort. Let's so let's see what you want to say about this. Yes, that such a service is not in place and it's not in our short term plan. But Victor is right and we have everything that we need, we just need to maybe to plan it and see how we can how we can do it. Yeah, thank you. So the question for this block keyword search does not work well in my field. Almost anization specific field also journals are not very informative as we are just a small field. And is anyone working on building such communities based on initial lists of publications where authors and references can show clear what belongs together. I think we already, I think tells something about the way that we organize the content I think the COVID is a good example but we will have more examples in the coming use cases but maybe you can explain a bit how it works and this. Yes, yes, because I'm to, let's say bootstrap a community gateway. What we Victor says is exactly what we do. So we start by asking the community, which are the projects that are relevant for the community, which are the list of sources that are relevant so if there are specific journals to include. And also, we cannot specific a specific list of publications as a start. And this is very useful, for example, also for the mining. Because if the mining starts by analyzing publications that for sure are related to the community. The level of precision and recall that it reaches is much higher. Okay, so now it's time to. So you can also provide more input if you will think that you find something more to say in the shot. But I think we have answered these three first questions. I will address other questions in the future also about with this Washington is already here asking also but let's move to the second part at the end of these six presentations. We will have time for questions and answers so please comment in the shot or write it in the Q&A directly to the speakers. Is this an introduction or can I ask the Nazis to to join us for this first presentation so we will have six use cases, and we start with Alexi Greece. And then we have Vergulis from from a dinner research in the innovation center and also representing Alexi agrees so you can present yourself and then have the presentations, we want to have kind of presentation seven eight minutes in order to find time at the end to for discussion and for questions so the Nazis you can share your screen. Okay thank you very much. Perfect with the sound. Okay. Okay. So, thanks for the introduction. I'm from us for good reason, scientific associate at the research center in Greece and a member of the elixir Greece community. And before we start talking, let me explain what elixir Greece is. Elixir Greece is the Greek node of the elixir as free European research research infrastructure. This is a research infrastructure that counts nodes in almost any European country, and it is about by informatics and life sciences. The Greek node contains consists of about 15 members research centers and universities that have groups that are very active in the field of bioinformatics and life sciences. This community was selected as a huge case for the open air advanced open air connect platform and the result was the bootstrapping and the customization of the dashboard for the Greek node this is what I'm showing right right now in my screen. And the first stage was to collect together information that was relevant to the people of the Greek node. And this was done both by providing an initial list of publications that have been produced by these people. And also by using text mining techniques in the open air data. And also, we had to provide a list of a list of official acknowledgments acknowledgement statements that the people in the community are using. When they publish research that is relevant to the projects that found this community. So, we had at first we had to collect publications and software tools of these people and provide an initial list and then identify those text mining rules that could include in this dashboard, even more results. And this was done with the core text mining team of the open air with their collaboration. And the result was the content in this dashboard. In addition to that, we had some extra requirements. For example, since members of this community had had a previous experience using a couple of indicators for scientific impact. We tried to integrate the scores based on these indicators in the interface of this dashboard and you can see this it was implemented by adding two buttons in each of the publications record that after clicking on them. Someone can gather information about how popular or how influential is its article. These two scores are based on a particular citation based analysis algorithms. Each of them capturing a different aspect of scientific impact. And after clicking on this pop up button someone can see also some visualizations or some details about the particular publication. And also, there is a color code. If the button is gray then this means that this publication is not exceptional in the context of influence or popularity. If the color is green then this is an indicator that the article is very popular. And more or less, after additions like these, the platform was ready to be presented to the members of the LXRGR community and a couple of months ago Alessia presented the functionalities of the gateway to the members of the LXRGR community. This was a training event. Due to the COVID-19 situation it was an online training event that was co-organized by RDA and LXRGR and OpenAir. It was a broader event about open science but it had also a dedicated session for the presentation of the gateway. And I think that the participation was really good and the members of the community, the final version of the gateway was presented to the members of the community. And before I close, let me say a couple of words about the next steps. First of all, we are ready to discuss and to help to assist if there is the need that these indicators will be included to other gateways as well. And also, in the context of another project we work for the LXRGR community, we will try to add in the next few months a connection between the official platform for on-demand computations that this community provides to its members. This is a cloud infrastructure that any scientist can run here experiments, computational experiments, and we will provide a connection because we will add the functionality that the scientist can define her own research objects, which is something like an experiment that contains a package that contains the code, data, and the configuration, and maybe also the publication, and this we will try to list them in the dashboard as well. That's from me. Thank you very much. Many thanks. Many thanks. So let's move to the second use case. So, Erzebet, if you want, you can start sharing your screen. We will have a presentation from the Daria open science officer about the way that Daria is in fact interacting with the open air. They share your screen, start and then we will have, after the six use cases, we will have questions. Okay, I can see, I can see your slides. Share, I'll show your camera. Yes, yes, yes, I needed to unmute myself first. And yeah, I'm sharing my screen. Can you hear you? Yes. And sorry, maybe I just quickly move to another room. It's one second. Okay. Just give me one second. This one. Okay. Sorry for this inconvenience. It's, it's a, it's a COVID use case. Okay, so now I can, it's a genuine one. Now I can, I can share my screen with you and now you should see. So, let me just switch to presentation mode and so hello everyone and welcome. Thanks for joining us for this session. I'm Erzebet Totsifra and I'm representing Daria. Daria is pretty much the equivalent of Elixir. It's the same type of European research infrastructure, but in another disciplinary field that is arts and humanities, especially what we call digital humanities. And so you think you can share your camera? No. My camera. Well, yeah, wait, wait, wait. It says you cannot start your video because the host has stopped it. Hold on, Erzebet. Go ahead. I'll try to fix this. Okay, perfect. Okay, just let me know when I should switch it on or you know what, now I'm able to do this. Yeah, after all the room changing and the video issues and everything so we can get started. Yeah, absolutely. So, yes, now you should see both my face. Absolutely. I truly believe that like as a humanist, especially more. Um, so Daria is the research infrastructure, European research infrastructure consortium for arts and humanities. And we were super glad to have the chance to collaborate with open air on making all kinds of research, research outputs visible, because the challenges that Alessia mentioned at the beginning, like the addition of research outputs across the web across publishers across repositories. Some of them are still sitting in our computers is even more an issue with the humanities, especially so because we don't have really domain specific databases there is no humanities equivalent of PubMed that is no really humanities equivalent of archive. So, and the outputs of our research is even more if you know hidden like even difficulties, much more serious difficulties to find and access and reuse the different content. Because these are happening in smaller contexts in smaller channels in smaller repositories, multilingual ones. So, yeah, we have serious discovery and reusability challenges. And so, unsurprisingly, these challenges that are domain specific arts and humanities specific are, of course, reflected in the smaller context of Daria as well. So, it's not an easy task to, you know, keep track of all the Daria affiliated research outputs, all the content coming from our repositories, all the publications when Daria is mentioned. So, we found it especially exciting to to have the chance to build something that goes against this and lay the grounds for information management system that goes beyond the scope of publications because we also see that research data research software will not be properly evaluated will not be properly assessed and rewarded by academic tenure promotion criteria, unless they are visible in an information management system unless people can sufficiently include them into the CV putting a discovery environment along with the publications. So, so we were super enthusiastic to see the solution of the open air research community dashboard. And so we wanted to build a discovery environment that is inclusive with a variety of content types that are important for arts and humanities scholarship, but are typically excluded from, you know, this typical book bibliometric databases. So, what we did I quickly take you through like how we populated the Daria research community dashboard, I forgot to tell you like Daria.open.eu, you can go there and visit but it's still under construction, serious volumes of content are about to be added in a coming days so I would suggest you to take a look now and take a second week later, so to say. So what we did is that at my organization Daria we have quite strong open access policies, and we don't only you know preach about open access and how to do this but also also give infrastructural components to really realize this so we have a we have a Daria collection on the French hall repository and we also have a Daria connection on the Zanotto repository that Alessia already mentioned. So, in populating the open air Daria community gateway. It was the very first step to find these collections start mining these collections, mining them for Daria content and add the content to the dashboard. The second step was a little bit more data oriented. We wanted to do this pilot with two flagship Daria data services, the French social sciences and humanities data repository in Arcala and the German repository tax grid and build interoperability frameworks with the open air systems so that open air can harvest them and can add them to the community dashboard, the Daria open air research community dashboard. It was a very interesting exercise and I think it's super important to organize this discovery frameworks not only nationally but also thematically and address domain specific challenges that we have for instance developing this metadata in the crosswalks. So, what you can expect to lend in the Daria open air research community dashboard in the coming days is humanities data at its finest you may wonder what is this. It's images. It's digital critical editions. It's newspaper collections. It's encodings of different shorts. It's encoded musical sheets for instance. So very diverse and very interesting content that will be visible in the dashboard is research data. And the first step, first step, we also wanted to be this dashboard also wanted this dashboard to be compliant with our internal publication monitoring system. So, to this end we have a sort of library that queries all the publications indexed by Google Scholar where Daria appears so all these publications lent in a sort of a collection. And after a bit of a manual semi automated half manual half automated curation we select the really truly Daria affiliated once, and we also started to add these publications to the open air Daria dashboard. So, on the long run it's also going to be fully compliant and visible and searchable and enrichable in the dashboard. So, what we learned to tell you a little bit of our experiences and working with open air. The first one is probably the most important one. It's super important if you want to be open open science and open science discovery frameworks to be inclusive with all disciplines. This is a challenge to do, but this is a challenge first to do because open science is not enough to be open but all the disciplines should be there. It should be equally open equally inclusive with all knowledge areas and this is why we are super grateful to have humanity scholarship on board in the gateway and in the bigger part of the open air research graph. Building metadata crosswalks. It's not as one directional processes one would imagine it's not about the developers of these data services just set up a crosswalk and that's it so it was super important for us to have a stillies to have a support team who helps us from the open air team and they come back and forth and align and then realign and then realign. So if they are building bridges between smaller and bigger systems smaller and bigger data services then people need to stand and you know collaborate from both ends of this bridge and it was really nice that we got this support from open air in the framework of a funded project. What else. Yeah interoperability is like a translation so we are using common denominators which means that of course a certain integrity certain richness of the original content will necessarily get lost in translation. So why we found it really important that open air is super transparent about provenance information like there is a clear. It's very clearly displayed where the content is coming from what was the last update and linking back to the original hosting and so on. And I think that's it from my side and maybe a little bit of of a practical update next week we are going to introduce the dashboard to the open air community. So if you want to learn more, you are very welcome to join us. And we are also going to publish the orbit more detailed case study soon. So thanks a lot. Great many things and also thank you for sharing this also invitation at the end. So questions to her but so you can put it in the question question and answers so let's move to a third presentation unless you. You don't you don't need eight minutes so you can start already so let's move to the less easier representing digital humanities and cultural heritage. They were not available to do this presentation at this time so Alicia. Yes, I will briefly show the digital humanities and cultural heritage gateway that we have set up. And I really like the idea of presenting this after the diet representation because as this presented the digital humanities context from the infrastructure point of view, but then data. It's just a part of the content that is available in the digital humanities gateway which is indeed a automatic gateway which now shows more than five millions publications so and this tells you how much active is the digital humanities. Researcher research community. And in fact, here we still, we still miss the NACA line text with content to which will father nourish the this gateway. And here you can see a part of the configuration that we used. Thanks to the suggestion of a killer Felicitti from from pin, which is the main, the main creator of this gateway. So we have a list of projects from several founders from the European Commission to the Italian ministry, the old RC UK. Australian funders and, and many others will have to be added. The main content providers that have been selected for now are the archaeology data service and some journals. They were selected by by a key lens collaborator and finally 20 Senado communities that we could identify as relevant for the domain. We did a lot of work on subjects. Which really helps us identifying, for example, interesting connection between cultural heritage and marine science because of the vessels that are underwater and that are interesting for from both point of view, from the point of view of marine science and how, you know, the fishes and all these things grow in the old vessels under the sea. So I said this, a work in progress. I mean, it's already a production gateway, but it can be further improved. So we started it during the open air connect project with PIN PIN from the University of Florence. And we are continuing, we are enhancing the contribution in the context of the Arab necklace project with which is an infrastructure for archaeological research, and you will learn more about these afterwards in the session dedicated to the collaboration with And this ends the brief overview about the digital humanities and cultural heritage gateway. So I think we give floor to the next speaker. Yes. Who is Claudia. Claudia. Okay, thank you, let's move. Okay. Hi, can you hear me. Yes, perfect. You can present yourself. Yeah, thank you. Hi. My name is Claudia. I'm the senior program manager for Easter. Eric is the European research infrastructure for structural biology. We are a distributed research infrastructure. We are a landmark. We have a lot of research infrastructure and I know these are a lot of acronyms. So if anybody has any question about what any of these mean, please, please ask me, but one important point of that all of that description is that is that distributed research infrastructure. And what it means with this is that Easter have 10 different instructors around Europe with 23 facilities. All of these can be visited or samples can be sent and access it remotely from all the scientists in all our member countries. We have 15 members, 14 countries plus EMBL and all the researchers can openly use our infrastructure. We can get funding to visit for travel costs for sample shipping and also for the equipment consumables all the needs from to do your experiments. So this is our main activity to provide this research visit or remote access, but we also have activities in R and D funding training internships, and you can read all about this in our website that I'm going to rush a little bit through this then we have more opportunities for questions. And I want to just to show you the sort of equipment I'm talking about what is in our catalog, because the state of the art equipment that we offer does translate in high profile publications. We have thousands of publications already. And this for us is our most important KPI is the way that we like to represent our output the best then this is a very important point for us. How we do this. What do we need of this publication library. What we need is to identify and collect all the publications that acknowledge is track Eric. And not only the publications, we also need to mind the publication metadata, what the paper relate to which project, which country, which funders with who with which collaborators. And another point of interest to us is that we would like to link is track Eric publications to the data repository. We take fair data, very seriously in instruct. And this point to be able to link publications to data repositories is a very important part of that plan. What do we do with this information. We use this information for reporting reporting to the Commission reporting to Esprit reporting to our national funders. I'm also reporting to this our scientific community. We also use this information for communication with big highlights from the publications and we show scientists this is what is available to you. We use this camp and use and use our infrastructure. And we also use it for service optimization. We have a look at what works, what doesn't and keep our catalog up to date and always improving. Then, let's, if we go point by point, the first point is how we identify and make this list of publications. This is the how we do it at the moment, we do it manually. We ask when a person upload their proposal in our system. But as part of the term and conditions is that they acknowledge instruct involvement with this set with this sentence that has in strike Eric in it. And then manually we search Web of Science or PubMed or Google search, either for Easter, Easter kidding to look for all the papers that have acknowledged Easter kidding. And then we have to manually verify each publication. Why do we have to do that, because we have a lot of false positive and false negatives that we need to try to avoid in Web of Science. For example, we pick publications that have acknowledged instruct either in the funding in the funders or the acknowledgement. But if there is no funder field, it goes to the acknowledgement. But if there is both funder field and acknowledgement, only look at the funders field. Then if our researchers have by mistake put our funding in acknowledgement, this is a false negative. In PubMed and Google search, we get false positives. If we were to look for instruct, we will get hundreds of thousands of publications. Then we only can put instruct Eric. And in that point, we miss some of our publications. These are just a few examples in green of the things we want to count and in red of the things we don't want to count. The first one in the top left is a perfect example of what we want. The user have acknowledged instruct and has tell us what is the proposal ID that relates to the publication and we can advertise this properly. However, the other two green have used only instruct, not instruct Eric, then it can be missing some of the searchers. And the ones in red are cases of other Corison 2020 projects that have instruct in the name, then this can give you false positives. Then what has been our collaboration with OpenAir? We see OpenAir as a possibility to improve our mining of our publications. What are the advantages we see of using OpenAir? The advantages we see are the publication for a larger number of sources that we do. Then this will make sure that we lose less publications. They also have a detailed mining algorithm that will help them pick the right publications. In the last few years we have been working together with OpenAir to improve this mining algorithm. We have shared with OpenAir our manual mining of the literature and they have shared their mining results and we have been working to improve from both sides. We also see as a great advantage the metadata mining options that OpenAir provides with projects, with countries, with funders. We see it as it was mentioned before by another panelist, the transparency part of it, using an independent resource to produce a KPI, we see it as a great advantage. Obviously, as you can imagine, the time-saving element, this is a very time-consuming to do it manually, then using OpenAir will be great. But there are still challenges that we face. We need to make sure that the mining algorithm avoids false positives and false negatives. I want to give you just one example of this. It's great for us that we can look for the result of the projects we are involved in. This is a collection of projects we are involved in. But not all the results coming from those projects involve instra-caring resources. Some do, but some of the publications are from our partners, are not instra-caring work. Then this means still some work to make sure that we are not counting publications that don't really relate to us. Again, it's great for us that we can look at and filter for countries, for funders, for communities. We haven't found, and maybe this is us, and we will appreciate very much your input, we haven't found a way to extract this information properly. We see it in the site, but we want to be able to export it, to be able to present it to our funders in a different way. We are looking into this, and we are still working on that. Another element that is crucial for Instra-caring that will be great to work together in, is that OpenAir gives us the opportunity to see that some of our publications link to data repositories, like the PDB. But still there is no filter option to just select the publications with those links. That will be of great help to us, because we want to encourage our users. Again, because this relates to fair data. Finally, I would like to acknowledge the collaborative work that our team in Instra-caring and the OpenAir team has done together in the last few years to go improve our mining of the publications. That is so crucial for those projects. And I would like to use this last slide to show you how important it is to these KPIs to be able to mine them automatically and non-manually. There it says that we have 958 publications. That was true when we did these slides. We have over 1100 publications now, and that has not been updated because it's done manually. And this is of great importance to us, and we are really looking forward to future collaborations. Fabio, thank you very much. Great presentation. Thank you very much. So let's move to the, just to tell you that we have two more use cases. We are managing quite well at the time. IPUS, now and then the Sustainable Development Solutions Network. So Michele, Michele, you can, Michele Manunta, representing the year IPUS, you can... Hi, Pedro, since you're here. Hi, Michele, you can share your screen. Can you see me? Perfect, perfect. Okay, thank you. You can present yourself. Okay, from the introduction. So I'm a researcher of a CNR in Italy, and I work in the development of algorithm for processing satellite data and to retrieve information about our planet. I'm IPUS, I'm the coordinator of the space segment of the IPUS research infrastructure. And in particular, I'm the coordinator of the thematic core service satellite data. So let's start just with a few words about IPUS. IPUS is a pan-European research infrastructure in the context of solid earth science. In particular, IPUS aims at to sharing and providing access to the facilities that have been built in Europe in the solid earth science. In particular, we want to provide a single access to the distributed research infrastructure that we have in Europe. So the users can access to the data, to the product, to the processing service and also to the software that has been, let me say, built and developed in Europe in this context. IPUS involves 25 countries. We have several international organizations. We have almost 250 national research infrastructure and thousands and thousands of instrument laboratories and terabytes of data and so on. IPUS is organized in communities. We refer to each communities as thematic core service, TCS. So we have the community of the seismologists, we have the volcanic observatories, GPS data, near fault observation and one of these community is the satellite data community, so the TCS satellite data. The TCS satellite data works in strong cooperation with the European Space Agency, so Space Agency, so we can benefit from the support of the visa. In particular, our, let me say, gateway access point is based on the Juaze Exploitation Platform that is a cloud-based platform developed thanks to the help of ISA. Within the Juaze Exploitation Platform, the user can navigate, to search data, product and processing tools, but most important for us is that the JAP, JAP is the acronym for Juaze Exploitation Platform, is, or provide machine-to-machine procedures, so API, mainly based on OGC standard and procedures, so the JAP platform is directly connected to the IPOS central lab. So the user accessing to IPOS can access to our data, our product, and can integrate the satellite product also with the other communities product, with seismological information, with GPS information and so on. So it is the, in my opinion, the most important idea of IPOS also to integrate data and product coming from different scientific community. Within our TCS, we can provide, or the research infrastructure, provide the systematic processes, so we provide data and product, but also we implemented on-demand processing tools so the user can, through the JAP access to a web tool to process, directly process the satellite data sector. So, which kind of data we are going to share, to distribute to IPOS. Our information, our product, are mainly based on comparison data, and in particular we work with the radar satellite images. Thanks to the interferometry, SAR technology, we can measure, we can detect and map surface deformation that affected our planet with a centimeter to millimeter accuracy. One of the most important application is related to the AIRPEX events. So in case of an AIRPEX event, we can map the centimetric deformation that has been produced generated by the seismic event. In this slide, we have some example relevant to some seismic events that you could read between 2017 and 2019 in the world, and this data can be, so this information about the surface can be easily integrated with the information coming from other communities and allows the user to study the dynamic that drives our planet. But benefiting from a large data set, we can study not only single event, as in the case of AIRPEX, but we can analyze the temporal behavior of surface deformation. In this case, I'm showing you the mean deformation velocity map relevant to the Europe territory. In this case, we can study and follow the temporal behavior of several kinds of deformation. For example, here we have some plots from the top in the clockwise directions, we have the two mines on the top, where we detect more than 40 centimeters of total deformation, then we have a landslide on the right relevant to the black sea. And then on the bottom, we have an earthquake on the right, relevant to the left Kada Island, and the Campi Flegre Caldera that is one of the most important volcanoes in Europe and is very close to my institute where I'm now, so we are located just in the middle of an important active volcano in Italy. And then on the left, we have some human related effect because they are seasonal, they are referring to as aquifer exploitation and underground gas storage. So this deformation are relevant to human activities, so they are very important for the impact that they can have on our security. But as already said, within E-POS, we are distributing also processing tools so the user can access and can navigate in the web in the job browser, can select an area, analyze the available data set, of course, and speaking about satellite images, and select a data set and process, directly process this data set within our infrastructure. Here we have an example relevant to the black cell region, and the user so in this case can provide the process can access to processing on demand. And this is the context where we establish a cooperation between E-POS, so the satellite data, the MACD core service, and the OpenIron initiative project. In particular, we modified the workflow of our processing tool in order to include the possibility for the users once they have produced the data, so they have processed the data to publish this data within the Zenodo platform. And we included, let me say, the publishing step. It's important that this step is totally transparent for the users, so the users don't need to create an account within Zenodo, but they need just to provide some information relevant to the metadata. For example, the owner of the product, a short abstract or some information relevant to the institution, and then it can public and make available for the community the results in the Zenodo platform. In this way, the user can share the science, for example, if they are going to publish the data set in some papers or in the project and so on. It's important, in my opinion, that the data set are directly published in an E-POS community within Zenodo, and the procedure is really transparent for the users. Of course, then we have the retrieval of the data set that are published within Zenodo within OpenIron. So in OpenIron, we have the E-POS community dashboard where we can recognize publication software and also research data set. In this way, we can follow, of course, the impact of the activities of the users, of the scientists in the community by recognizing publication and so on. So this was my last slide. If there are questions, I have to answer. Perfect. So many things. Let's move to the last presentation. Okay. Akilesi is already connected. Akilesi, representing here the use case of the Sustainable Development Solutions Network. Can you start sharing your screen? Can you? Yes. Can you hear me? Yes, I can hear you. So this is the last use case, then I already saw that several people are asking and we are providing the answers, but you can also ask questions and we will answer after this presentation. Akilesi, the floor is yours. Pedro, after Akilesi, there is also Haris from Martina Research Center that will talk about the Sustainable Development Goals in the OpenIron construction. Okay, so let's start. Yes. If you want to share your camera also, it will be better. Perfect. Now you can start. Great. So on my side, my name is Akiles Vasilopoulos and I'm an assistant professor at the University of Ioannina. And I'm also a senior researcher that I create, which actually was the partner of OpenIron Connect. And it's also one of the hosts of the Sustainable Development Solutions Networks Network for which I'm going to talk to you about today and our work in OpenIron Connect. So the Sustainable Solutions Network is all about the SDGs. It's a network, as the name says, a network of networks actually that has to do with the Sustainable Development Goals. And the Sustainable Development Goals are what the United Nations has set up as the main goals of humanity for 2030. It's actually the dashboard that presents everything that needs to be done by 2030 as the United Nations. As you can see in the slide, there is a wide variety of targets, no poverty, zero hunger, reduced inequalities, et cetera, et cetera. So it's a very broad agenda and it was actually the main change between the Millennium Development Goals and the Sustainable Development Goals. Because the Millennium Development Goals were targeted mainly on the developing countries, while the Sustainable Development Goals are targeted to all countries, developed and developing. So the SDG agenda has these 17 targets, 17 goals that can be broken down to 169 targets and even more to 230 indicators. One of these indicators, and there's a reason why I'm saying that, is research done on each of these 17 goals. So as the Ban Ki Moon, the UN General, said it when the Sustainable Development Goals were presented, is that the Agenda 2030 compels us to look beyond national boundaries and sort of interest. However, to implement the Sustainable Solution Agenda, the idea was that we need the network that will be both global but also will have local hubs who will be responsible to guide the local authorities but also to observe research and what is done in this framework. So the SDSN was set up in 2012 by the UN Secretary General Ban Ki Moon, it was meant to mobilize global scientific and technological expertise and to support the SDGs at the local, national and global scales. So this is why I said before that the SDSN is a network of networks, because there's a big network, the SDSN global, and then we have national and local networks like SDSN Greece at the local level but also regional ones like SDSN Europe. And they all collaborate to target the specific targets. So more than 20 national and regional events are already launched and the SDSN Greece was one of the first to do so. We were very happy to be engaged and to host the SDSN Greece and we have more than 30, 350 member institutions over 80 countries. This is our website so feel free to browse and have a look at our work and what we are doing in terms of achieving the sustainable development goals. And the UN SDSN Greece is part of a cluster of institutions here in Greece, including the European Innovation and Technology Climate Kick, the RISC research center that is based on the Athens University of Economics and Business. And it is doing research on socio-economic and environmental sustainability over many years now. And the climate kick which is the Athena Research and Innovation Center is the host and is led by the director is Professor Fitbit Konjuri and it's also one of the hosts of UN SDSN. So far, the SDSN Greece has more than 50 public and private universities as partners. NGOs, we have strategic partners like Ministry of Environment, the BAF Greece, Greek National Research Center and we have collaboration with critical strategic partners. So what was the idea behind us getting involved in Open Air Connect? We wanted to create as the reason for SDSN to exist is to create a hub for all the research conducted in the local boundaries. So all the projects and all the papers that are related to sustainable development in Greece. And we wanted to create this platform, this repository that everything will be collected. So this is the research site. And this is our community, the community dashboard where we already have 9,800 publications and many research stuff, et cetera, et cetera. And it sounds huge and it has a reason for that. This is because as you saw in the SDG dashboard, the SDGs are pretty much about everything. So our work here was to collect publications, data and relevant documents about all the research conducted in Greece and put it in this repository. But the most important work and this is where Open Air Connect came as a life saver is to be able to search within this research, monitor how the country is going and link research outputs to specific European projects or funding agents, et cetera, et cetera. And this is also, and this is very important in order to monitor because as I said, SDSN has this role to monitor how the country is doing in the several SDGs. But also it's about having the role of the local hub. So being able to identify who is doing what in Greece. And this is actually our main work and the main development of SDSN in Greece. So the dashboard right now is to find ways to extract information for publications from institutions, from authors and be able to have them within each of these 17 goals. This will be of great help in two ways. First, because this is going to be a repository where everyone can get in and find out what he wants in terms of each of these goals. But second, it's very important for us because at the beginning when we started this join the SDSN community and we were trying to manually identify who is doing what in Greece, we found out that this is an impossible task. So doing it not manually but automatically with a bit of supervision, let's say, and with a bit of placing rules here and there is of great help. And it's also a very important for SDSN in general because every now and then we have the SDSN dashboard. So we provide data at SDSN Global saying what how the country is doing in each of these 17 goals. And as I said before, one of these how the country is doing is how much research is done in each of these goals. And this will be very easy for us to collect when we have the dashboard fully developed. And how do we do that? We are trying to populate a list of keywords for each SDG. It's not easy. So we're trying hard. And we are putting more and more every time. And this is how the different publications and the different projects will be categorized. And then how the information like authors like universities like recent centers will be extracted. So we can have this, this greater overview, this great overview of everything that is going on in Greece and be able to understand who is doing what. And this is related to what we say as sub community. This SDG will be a different sub community, let's say, where it will have the very active partners, the very active researchers, the very active institutions and they're not so active in this field. Of course, this will be useful for us to actually be able to have all the relevant information for our network in Greece, but also for everyone else who will access the dashboard like the policymakers, scientists, other scientists, etc. So that was it for my part. Thank you. And if you have any questions, I'll be happy to answer at the end. Okay, great. So let's join now all the, all the, let's use three minutes and then we have a presentation from Harris. Okay, okay. Every story, very much. Sorry. Hello. Hello. Hi. Okay, we can see you. Okay, thanks for having me and for an invitation to the open assembly general assembly. I'm Harris Papa you're you coming from a ten I research center and from the Institute for language and speech processing I'm a research director in the Institute that I have been working in artificial intelligence and language technologies speech language. I've been here with the kids. And I'm very keen on using these technologies in various areas in various domains. And definitely for SDGs, which I will briefly present our developments for SDGs and how we plan how we try to bridge open research outputs to SDGs. May I share my screen. Please do please do. Yep. Do you see my screen. Perfect, perfect. That's you can put in presenter mode. Okay, briefly about the best tracking SDG developments and as I said how to connect open air findings open air research outputs, data sets publications projects and various entities like the beneficiaries organizations and the research labs and the universities that have participated in the projects and bringing various facets and aspects like visualizations per country or per funder per program and in the timeline across time. So, we see this this problem this task in as a three step process as in three different discrete phases. The first step is how to classify all these research outputs according to SDGs. The second is about how to to bring evidence about the innovations at the outputs of these open air research outputs in related to SDGs and what might be or is today the impact of these innovations in terms of the indicators in in sustainable development goals. The methodologies human in the loop approach where we integrate technologies artificial intelligence technologies in an efficient effective way in the open air graph. It is granular and scalable that can process thousands of research outputs, and it is applicable to all SDGs. So the first phase about SDG classification. All aspects here is that we have a starting point here as I said is the data found in the open air graph, and by doing a very preliminary analysis on term extraction was everybody does we extract some very good keywords automatically, and we build a graph, we build a graph and then we apply some machine learning graph machine learning graph deep learning techniques in order to to to to to connect connections and bridge these research outputs to specific SDG targets. So what is what is what is the question here that we try to address is what is the problem, what is the SDG target that research output is related to, or try to address to an extent. By doing this we connect research outputs to specific SDG targets not only SDGs in general. The second phase is is is trying to to to answering the how, how do these entities, the researchers, the scientists, the labs, the universities and the companies how do they envisage the potential solution to an SDG target, what do the scientists or organizations propose. So by doing this by in trying to answer and to addressing these questions. The idea is we dig into the output of the first phase, the outputs on from the open air graph. This is a publication that has the title health and well being of secondary school students in New Zealand, and the trends between 2000 went up to 2012. And we, and by applying natural language processing techniques we identify the topic what is the research output of this publication if it is a study or a treatment or a drug or whatever, according to the taxonomy of research outputs or the publications. So what is the evidence that the scientists bring about the topic and what is their claim in the final in a sentences of the publication abstract you can see that the authors claim that they have been important improvements in the health and well being of New Zealand. This is very critical because we want to support and isolate this claim sentences and the sentences bring these sentences convey a message about the innovation. What is the innovation about this publication in the same spirit and by the same token we use the same techniques in in in the project portfolios. This is a segment from the results in brief or an or an FP seven project, which is entitled transvak. And this is a company lion X what participated in that project and by doing the same kind of analysis we would like to isolate sentences where they mentioned, they mentioned a specific innovation statement like this is a drug this is a drug potential drug that came out of this project and this company participated in this project so this this fighting might also has brought in the market there is a drug in the market. And so this might have a connection or a contribution to a specific SDG target in health under health. And so we do this also in the company's website by visiting the web page of the companies we also test if there is a connection to what the publications that the open air research outputs revealed, and if there is a connection to what this company's mentioned in their web page as their products or their services today related to the SDG. And by doing this we we also connect the dots we also connect the innovations and the relatedness of these innovations to SDG targets. So we know that there is a there was an outcome of this project that was related to SDG health three and for a specific for a specific target under SDG three at this company benefited from participating in this project brought in the market a product which is related to this SDG. So this might be a good good thing how they approach SDG three at the third phase the last phase the last step is to do a short of data analytics and try to for impact and tracking progress and correlations with other data that is already there. So the question here is what was the impact of a contribution to the SDG progress plan and how can we correlate all these innovation findings with indicators in with indicators mentioned in in in United Nations. On the left side of the slide you can see that they're about renewable energy, the progress, the share of renewable energy in Spain, spanning from 90s up to 2017. On the right side part of the slide you can see the innovations that we have traced for renewable energy in the in those in those years. Can we find some good correlations, justifying that these innovations, somehow contributed to the progress that was made in Spain. And we also forecast and predict what will be the future in the next coming years. So this is data analytics stuff here and it is the third step of what we plan to do by bringing open air into the SDG go business. That's all for me. And thank you for listening. Great. So many thanks for this presentation. So Alessia, do you want to to highlight something. So I asked also the others to join let's use only one or two minutes I see that the, almost all questions were addressed and replied directly in the chat, but I think, even if we will finish. Five, 10 minutes later, I think it's important. So is there is something that I feel that all questions were answered. Do you see something that you need to to highlight from the reply that you gave. So cloud questions to her, but to Alessia to do you want to highlight something in some seconds. We have a question that relates to to the discussion about the open air graphs. I've been involved in the project called Freya that creates a persistent identifiers graphs. And I was wondering if you can enlighten us about if they have been any collaboration or any talks or in the aspect. Thank you, Claudia. Yeah, Alessia can can reply. But yes, there is collaboration. Yes, there is collaboration within open air Freya data site arcade and the Australian research graph. So they are all initiative in different part of the world or international. And we are addressing the same issues from different point of view. So we, we, we are connecting and we are trying not to do the same things twice. But to, you know, do things in synergies and exchange information and exchange experience and on engaging the people working on on scholarly communication and what we can call now scholarly communication graphs. And we are also having an RDA working group on this colleagues framework for exchanging the links between the data sets and publications, and also on the PID graphs. So there is collaboration between us. Yes. Great. Let's say thank you. So is there anything that you should highlight that we have one question here but we will answer in the shot. I think it's. So there are also two questions in Spanish that we can reply here in the shot that them. Elizabeth you want to ask something to highlight something from your reply. The Nazis. Everything was clear from the I was trying to I was trying to answer the target relevant questions and and all of them were super interesting so thanks a lot. I think our collaboration with Europe, you know, it's again a yes. So we find it really important similarly to what or how Alessio highlighted the collaboration with the related institution initiatives and projects not to, you know, duplicate the efforts with coordinate wisely. So we have national level collaborations with Europe, you know, the Daria Ireland and Daria Greece are the strongest allies with European in this respect but also the European level Daria EU we have several location to collaborate on advocacy on research data management, including a cultural heritage data and culture sector and the siloing these two big institutional frameworks and also we are frequently joining forces on the policy making areas. I added some links to the to the answer. Thank you very much. I don't see any other any other questions so I think people are happy with the answers that you have provided. Let's do a final final check if there is something that is relevant or not and we can move to the next session. I don't think we have more more questions. So stay with us don't leave so we will finish 10 minutes after the time which is not good for a Friday afternoon but I know that you this session is being quite interesting so who will start I'm not sure Alessio or Eric. So final presentation on some of the collaborations in fact, these are also use cases that we want to highlight and in fact based on projects collaborations so European projects that are working with open air as a as already a legal entity more than a project so Eric please the floor is yours. Stay with us don't leave us. Hello everyone I'm Harry from Athena Research Center and representing open air here in these projects. Let me share my screen. Let's be open first. Okay. Okay. Right. So be open is an open air collaborate sorry open air is collaborating with the be open which is the European forum and observatory for open science in transport. The project that started in 2019 horizon 2020 with a budget of under two million. And it has 17 partners which are key players in the transport in different transport modes of different transfer or in open air and open access and open sorry science. So what is the vision of the open is to create a common understanding of the practical impact of open science and to identify and put in place the mechanisms to make it a reality in transfer research and it's doing that by setting up and implementing topos which is the transport observatory and forum for promoting open science. So promote regulators that arise open science aiming to develop a framework of common understanding of open science in transport. A map existing open science resources and see how they applying transport facilitate an evidence based dialogue to promote and establish open science in transport and provide a policy framework and guidance. Again for open science implementation transport and engage a broad range of stakeholders in participate process for open science update. And it's the projects organizing different themes that basically to standardize regulate and promote open science in transport. Open air is involved in some of these work packages via Athena research center. So mapping the existing open science resources and sources in transport, creating a code of contact conduct on open science and transport and the topos observatory. So what has be be open done so opener done for be open so far where it's delivered the be open research gateway on transport research, which is a single entry point for discovering research products available in the open air research graph and relevant to the transport research sector. Its initial configuration was based on output of work packages one and two. And now it's domain experts from the consortium have taken over, in order to fine tune the configuration and open air supports them. And we decided that this will be part of topos observatory will be further development enhanced. And we will play the role of the observatory for organizations because there's also an observatory for individuals. So this is just a quick view of the research gateway. And this is the top all the links I will provide later in the chat. And this is the topos observatory, which has the blue part there for organizations with which at the moment links to the gateway in open air. And it's provided by open air and the observatory for individuals is provided by site media, and there is also the forum for exchanging ideas for stakeholders and this is the first time. It's been just presented and it's just a kind of the first slides of it. The different modes of transport and multimodal. And for each of them addresses different topics that are relevant. Now, in open air, we have document classification system which mines the full text of publications in order to perform content based classification using given taxonomies. So in open at the moment we'll be using some taxonomies but we don't have transport classifier. So the in this project we also want to create one based on the latest edition of the glossary for transfer statistics, developed by the United States nations, euro start and international transport form. So this has 10 categories. The problem with this that there is no annotator labeled corpus of publications in transfer research to train a classifier. And we'll be using some of the advanced techniques of Harris Papa year you who talked earlier, and, and seeding classifiers from the publications and metadata from the be open research gateway. More information can be found in the be open project website I'll share the links in a minute. And, and that's all for for be open. So do you want me to continue with us at me is at the end. No, no, no, please do it as well. Yes, please do all your projects. This is a sample of projects. Okay. Please proceed. We see that this knowing in the net and so, yes, let's proceed your presentation. Let me again see share the screen again to different. Okay, let's, let's hear this different examples of projects at the panel is collaborating. Okay, yeah. Okay. Yeah, yes, yes, yes. So open air collaboration with Ariadne plus which is a data infrastructure serving the archaeological community worldwide. It's a continuation of the Ariadne without the plus which is a very successful project that integrated European archaeological repositories and created a searchable group of data sets including unpublished reports images, images, maps, databases, and other kinds of archaeological information accessible online, more than 2 million records. And in the plus will extend the results along several several dimensions, while focusing on innovative services and embed Ariadne in the US, because being told we don't have much time I'll skip some of the details. So it grew from 17 partners to 41 partners covering 26 countries in Europe, plus international USA, Argentina, Japan, and Israel. And it expanded in several dimensions, both in temporal domain, and in geographical location so we'll cover now almost all of Europe, and it will go from pale anthropology all the way to contemporary age, plus in the science dimension. And by including more science topics and different archaeological things like we only had to draw chronology now there will be different dating and mechanisms and things like that. So it's expanding and the idea is to mainstream its objective is to mainstream data centric methodology in the ecological research community by creating a cloud based one stop shop to find an access and interoperable work or archaeological data and reuse them in a virtual research environment. So it's creating a the first level of comprehensive catalog for archaeological data sets, based on a share ontology and common vocabaries and goes into integrating in more levels on the item level that your reference level and so on so forth. And now the, the, this is the Ariadne website. And the links below there's also a link what is dot Ariadne infrastructure to you where you can find a lot of information. And from there, someone can access the portal, which has the catalog. Now the, the catalog is searchable according to three facets of when where and what. So by time space and object, and by keyboard drawn from controlled vocabularies. So here's like the what the different objects in the catalog. And now the collaboration with the opener is under one task called integrating archaeological digital libraries with Ariadne plus, which aims to link. And the Ariadne data infrastructure with repositories of scientific publications by exploiting open air and the links to individual journals. So the idea is make archaeological data more discoverable accessible interconnected and complete. And we build a bridge between Ariadne and open air. Well, in the previous pro project there was a very small pilot where we developed text mining citation extraction and matching algorithms, which was run on archaeology data service great literature reports excavation reports. And we only tested it on medical history in epidemiological journals so e PubMed can repositories and but already but even there found 300 relations, covering a broad archaeological kind of fields like anthropology paleontology and so forth. And these were validated by an archaeologist, which said that the vast majority of records were absolutely useful and relevant and even the director of ADS, Professor Jim and Richard said that, given that great literature is rarely well referenced in publications and connections is a positive result. So that went very well so in Ariadne plus we will expand that to by searching in all of the open air space and also using data sets from from Ariadne plus harvesting their metadata and see if publication site any of those so we will try to expand the relationships between the two, and which will be shown in both portals and could also improve the configuration of the digital digital humanities and cultural heritage gateway mentioned earlier. Another thing is we will be improving metadata of published papers by exploring the possibility of using the Ariadne plus named entity recognition service. And I forgot to say is that Ariadne apart from collecting all these objects and repositories and creating the catalog also has a palette of services that is developing cutting edge services. So the this named entity recognition service which was developed in the previous project by other partners from University of South Wales I think was based, was further developed into text crowd, a cloud based NLP tool, which was a science administrator within the US pilot to you project and there's the link. And in this task will be collaborating with the University of York and University of South Wales to see if we can use the that service to extract information from published from to enrich published papers. A final thing, it was a very interesting collaboration between open air and and Ariadne plus concerning data management plans so you know we have the August tool and they had an online template for data management plan, which was based on guidelines from Horizon 2020 and designing according to the Parthenos guidelines and but dedicated to archaeology to archaeology, our DMs, whereas we have Argos which is, you know an online tool, which offers many templates, it's based on open air DMP, which was a collaboration between open air and you that and it's in the interdisciplinary so we wanted to expand by adding archaeological templates relevant to the archaeological domain, and they wanted to learn from us and also use some of the benefits of Argos, which is like creating machine actual DMPs and linking two years components out of the box and things like that. So there is a lot of area that was covered and which is described in the blog post post and the link is below. Initially, there was a collaboration to see what were the tools that were available in archaeology for creating DMPs, so not only the one from created by Ariadne, so looking at the commonalities and differences of all these tools and how they applied aligned with fair principles and global standards, and then the both the Ariadne template and the Argos tool were enriched with guidelines for better navigation and literacy on our DM and the template. I mean the output was that the template is now available from the Argos platform based on the Ariadne plus DMP, but it's enriched with open air APIs that's providing you know the extra capabilities, especially for archaeological data which are reused and also enabling compliance with global standards. Argos can export now from DMPs in that format which I think that Ariadne is trying to create an importer so that they can use directly the output of us while keeping also their own DMP. I think that's it for now and thank you and any questions I'm happy to answer. Great. So, let's let's proceed the messages to have more to finalize briefly. Okay, let's highlight the other projects and then we can finalize. Yes, yes, I will be brief with the last three projects we are collaborating with. So one is a big data, which is a European research infrastructure for big data and social mining, which focuses on ethical and responsible research based on big data analysis. So they provide several exploratories where researchers can work with big data and do analysis on different topics. So on explainable machine learning on cities of citizens migration studies, social debates, sports, data science and well being and economy. Open Air in this project is the leader of task about the online science monitoring dashboard. So guess what, we are providing a gateway for the so big data infrastructure in order to keep track of the outputs of the researchers using the infrastructure. And all the outputs that were generated during the so big data project and also in the current so big data plus plus project. And we have also a connection with Zenodo because the exploratories which are basically virtual research environments will automatically on demand of the researcher publish their outputs on Zenodo so that we will end up also on the so big data gateway. And the official release for for the gateway of the project is December 2020. So we are almost there. Then we have any maps, which is the open data tool empowering your energy transition. So we are talking about sustainable energy. And you can see that the list of partners at the end of these of these tasks and you will find the links to the website and the social social media when you get the slides. So the objectives of animal maps are to have a single entry point where researchers, policymakers and all stakeholders of energy can find data sets and can use that so on the one hand they need a comprehensive view of the data sets on energy that are available. But they also need a place where they can analyze and visualize in an easy way that assets themselves. Because, as I said, the target users are not only researchers which are Giki, you know, you know a lot of things but they're also policymakers that need to see something clear and they have to see, you know, the outputs of an analysis and not the raw data as they are. And for this it's very important also to create the quality of the data sets and the quality of the data that accompany the data sets. So, in these projects, the importance of fairness and of the being able to interpret the data that is available is is very important. In doing as open error, we are the work package leader of the package about the nr maps data management tool. So, we are going to have a release of the open research gateway on energy research in January 2021, and this will be linked to the data visualization tool. And we are also giving our support on data fairness and openness and trainings that are needed for for researchers. And of course, we will support the integration of these community into the use the European open science cloud. RISES, RISES is our research infrastructure for science and innovation policy studies. So it started in 2014 with the RISES project and now we are with the RISES to project. So basically they are providing the so called RISES core facility that provides facilities, resources, services, software to researchers in the fields. And they are already very active in the open science ecosystem, say because they are already using Zenodo as a repository for the outputs and outcomes of the projects and the researcher using the infrastructure. They have a virtual research environment where they can run algorithm and access open data. And with RISES too, we will have an enhanced open data virtual research environment and we will offer the two dashboards in fact. So one thematic dashboard, which is a thematic open research gateway and one gateway instead for monitoring the outputs of the infrastructure. And this will all be connected in the virtual research environment they have so that from one single entry point they will access the created data sets that they are the other members of the projects are preparing and they will have also access to the dashboard that open research provides and the official release for this will be again December 2020. And yes, okay, I already mentioned the Zenodo community so let's go to the last slide because all these projects you have heard about today. They all contribute to the open air research graph, their researchers can use the open air research graph so if they needed for research, if they needed for analysis, they want to calculate their own indicators, they can take the graph and use it as they want because the graph is CC by and is made available for everyone. And we would like also to thank all the projects and also all the panelists that presented before for their help in having better and better false text mining algorithms that works well for them and also for the others. Pedro, this is a great way to to finish this session because the connect is in fact the service and this services that open air offer to research communities and research infrastructures but we can only build this services with the support in a kind of community effort so thank you very much. So, I see that there are no questions but every there is one question that I have already answered about if a specific information about Ariadne if it's already as free or Eric, I replied but if you have more information please be aware of that so please check it in the in the in the chat again the Q&A. And thank you for feel free to join us, Ari, with the with the beautiful view with snow in Athens. It's not but from what I know is trying to see how it will continue at the end. You're still a project. Okay, so as we have 19 minutes past the hour but I think it was quite useful and it was a challenge to have all these use cases and I think it was quite a benefit for this session so many things for all the speakers. Alessia and Eric thank you for this last presentation and Alessia thank you for all the great work that you are doing managing this new service in open air and for all the technical team they do a great job improving all the capabilities and functionalities of this service to provide a robust service for our for our users and for our communities and research infrastructure so thank you. We are coming to an end. Alessia, do you have something to say. I see there's a question. Oh, there is a question. Yeah, that connect is in beta when you expect it to be finished. Okay, this is important so maybe maybe it's good. If you do a kind of qualification in terms of timeline to have everything. In production, the service, could you clarify, Alessia, as a last information. Yes, yes, I can say that we have all the gateways are ready to are ready for production. They are not in production because we wanted to have more content. So now that we have it, we are ready to actually put them in production so not better anymore. And so all the gateways will be in production except those for the projects that we just presented because we are still working on them. So, the first release that I mentioned, they will be on beta, of course. And the last, they will all go in production and we use the content that is available so on explore dot open air dot you. Great, thank you. So now I know it's clear they were in better because we wanted to have our, the expansion of our graph now that we have this new research graph I think we. So everything will be in production so thank you very much. Thank you to an end sale thank you for those that resistance, the, that are here with us until the end so. In fact, whether it were we have five great days with all our five public sessions. More than 700 people attended to our sessions. So many things, you were part of that. So you are part of open air, you all are part of the open air community and to build a better world with the open science so thank you all. And see you next week for those that are interested in open access week. Yeah, open access week activities that open air is offering next next next week we are collaborating with several groups to offer some open webinars targeting researchers so be aware of that and see you in the upcoming activities so open air is here to stay. So, stay with us to build a better world with open science. Bye bye. Bye bye. Thank you. Bye bye. Thank you.