 That's fine. That's great. Thank you. I look forward to the chatting to you later. So thank you for joining this webinar. I know everyone's, there's so many webinars going on at the moment, everyone's kind of webinar doubt. In a moment, we're going to be asking you to kind of tell us about your role and why you're interested in ICM or information knowledge management, I should say. So we thought we'd kick off by, you know, it's only fair that we say this bit by why we're here. And kind of what brought us to this point in time. So I'm Julia Barrett and with Sikena Bawani, we run the We Adapt Climate Change Adaptation Knowledge Sharing Platform, which is a global platform. And that really focuses on building a community of practice, connecting people with relevance, material supporting, learning and knowledge sharing and networking in this field, really promoting that kind of community of practice between people. And knowledge discovery has been a really key aspect of this. We find that users really want to quickly and easily find related information and it needs to be really accessible so that they can best use it. And this has been, this has led to many collaborations and I'll just pass over to Sikena to say a few more words on that. Thank you, Julia. Great to see so many people online. Hello everybody. Yes, as Julia says, so Julia and I are from the Stockholm Environment Institute in Oxford at the Oxford Centre and the work that we've been doing over the past nearly 20 years around knowledge management and knowledge sharing has really meant that I came as a key feature of our work. So in managing the knowledge, the adaptation knowledge platform we adapt, but also in many of the collaborative projects we've been doing with some of you who are online, in fact, around adaptation. So many projects which there are many projects which have tried to catalogue and classify adaptation actions, such as the UNEP Proveer guidance, for example, which many of you probably have heard of, and precursors to that were things like the mediation path finder and even earlier than that were things like the ADAM project. And so there's been a long history of trying to classify and categorize adaptation action strategies, methods, approaches to increase learning between our communities. And what's often impeded this is a lack of standardization between how knowledge is shared, within how knowledge is shared, but also a proliferation of information and terminology, so the way in which language is used and the way in which language is interpreted is also a barrier often. So we have amazing case studies but often very little way to connect them and to learn from each other and this often leads to replication, redundancy and so on. So the project we've been working on for the past five years, I think some of you joined our final conference a couple of weeks ago is the placard project. And this is an EC coordination and support action part of Horizon 2020, which aims to promote better communication collaboration and coordination between the climate change adaptation and disaster risk reduction communities. And throughout this project terminology and language and the use of different terms and the interpretation of language in different ways was often raised as a key barrier to this collaboration and communication. And a big part of the project was how to strengthen institutions and institutional mandates to better coordinate action. And so this is why I came became a big part of this project actually. And so we had a lot of stakeholder workshops and dialogues to try and understand the barriers that stakeholders face in their day to day work and trying to fulfill their institutional mandates and addressing these barriers as really the driving motivation behind the work we've done and the roadmap that we are going to discuss today. So as a quick icebreaker and to see who's online we were wondering if everyone would be happy to switch on their cameras if you have not already done so so we can see who's in the room. That's great. And we thought we might ask you a couple of questions just as a quick teaser to find out what people are interested in terms of ICAM and how much they're useful or not. So one question. So you'll have your camera in front of you. So if you put your finger over your camera, some of you are part of the placard conference last week. So you probably saw us do this already. So we're just going to follow Margo's footsteps here. And so if you all cover your camera for the moment and uncover your camera. If you think you have some understanding of why taxonomies are useful. Quite a lot. And uncover your camera please if you're a knowledge manager as well. And if you're a user. You consider yourself a user of information. Okay, great. Thank you. Now the other thing we were going to do is I think Andrew who's helping us facilitate the webinar today has already shared this in the chat, but we have a Google Doc. The link is in the chat we have a Google Doc which is sort of a collaborative notes document for us. And there we were just hoping that you would be happy to share your a bit of information about yourself so I'm just going to share that on my screen right now. And so basically just share a little bit about who you are where you're where you come from and what kind of interest you have in IKM and why you why you're interested in IKM actually so that we can that helps us to reflect on whether this roadmap is useful and whether it's addressing the needs that people have basically. So I hope you can see my screen. And here we just have it's a collaborative notes document here and we just have a box here that says name job role country and what your interest in IKM is. And if you're happy to use the suggesting mode here in the Google Doc for those who are not familiar with it and just type your name and your role and what your interest is in IKM and it can be literally a couple of a sentence or two. This document is also important because further down we have some useful resources that might be of interest, which you can come back to after the webinar and also later we'll talk about different ways in which we can engage as a community. And there are multiple ways of doing that here so you can opt to opt in or opt out of that. If you want to add your name there. Hand back to Julia for my mic dies here and we're getting some so we can see some additions to the Google Doc. That's nice. Okay, so I'll hand back to Julia for now and she'll take us through the agenda. Great, that's fantastic. And I say we'll be sharing that Google Doc around all the participants and there will be a recording of the webinar available as well. So just a little bit of word on the webinar. So we're going to be discussing what we think the key information knowledge management challenges are what do you think is the best way to do that. And the bigger picture, so how shared taxonomy can set the stage for kind of smarter ICM and AI and this is going to talk about ontologies and a little bit about knowledge graphs, although we also have another webinar coming up in that. And finally, exploring this collaborative roadmap for how we can get there. And we're really looking forward to hearing from you about that. You know, what do you think of it? Did we miss something? Is anyone interested in working on that? You know, can we move forward together and what might the next steps be? So I'll pass back to Sakena to start kick us off about the ICM challenges and user needs. Thank you so much Julia. So the biggest ICM challenges we face at the moment and we have been facing increasingly over the past five years are the amount of data that we we are faced with on a daily basis and organizing and analyzing these vast amount of data is particularly difficult if there's no structure or common format or standard for this data. In addition to that, we have a fragmentation of information. We have knowledge scattered across multiple platforms, portals and websites, even though objectives of these websites may be quite similar. And this really leads to a deepening and hardening of information silos and the connections between these different strands of work becomes increasingly harder to make as more and more knowledge emerges. Additionally, we have these disparate terminologies that we've talked about communities often have their own way of describing things which are completely legitimate. But they often use different terms sometimes to mean the same things and this results in an inconsistency sometimes in the way things are interpreted and understood. And in adaptation and DRR particularly we often use different terms in different ways and this also leads to missed opportunities for collaboration. The increasing frustration for users in this is what's basically emerged from a lot of the stakeholder engagement that we've done so when we've asked users what they really need and what they really want. Some of the key things are around enhanced discoverability and searchability of information. So the ability to quickly and easily find things also to have fewer entry points between regional, national and international platforms. So finding content individually through separate platforms is also quite an issue. Additionally, sometimes having automated alert systems that inform people about new content can be interesting such as help desks or request services that are emerging more and more. Some of these are automated but again automation is really dependent on standardization. And as we mentioned terminology and language comes up again and again amongst both experts and non experts. So the thing that we feel has emerged as a key one of the key solutions to this. So to a lot of these issues is around the widespread use and development of a shared taxonomy within our communities. Taxonomies are collections of terms that together describe a topic area and they provide an overview of a vocabulary that's used and how these terms relate to each other. This is the climate tag a screenshot that you can see here and this is just one example of how the topic area is structured here and this is similar in lots of taxonomies. But importantly for us taxonomies are really important IKM tool because they provide the keywords that we use to tag content online, which helps us categorize content but also link it to other content online. So we use these keywords to describe papers reports case studies and make them easier to find and you can find these in action on lots of websites for example nature here. A key feature here is that the metadata that's additional to the taxonomy is really important as well such as definitions notes on term usage, how term usage as a term usage has changed which is often important in our area. And you can see here there's lots of related terms there's lots of related content and that's the power of the taxonomy here. Taxonomies are also often implemented in the in the background of websites so you don't really see a lot of that. The more technical stuff that's going on in the background, but as you saw on the nature website it becomes very user friendly. On the back end this is pool party software that we're using to help build a taxonomy for adaptation and DRR. And here the things that are important are things like the alternative labels or synonyms. So this is metadata that provides a way to connect data across different communities for example if one community describes EBA or nature based solutions in one way synonyms can be used to connect these things across different communities. You also have broader and narrower terms related terms definitions and scope notes and scope notes are very important because they describe how terms are used. But they also describe how terms are not used or how they're not used in this particular. So keyword tagging is already widely used across adaptation and DRR platforms and websites and some are live they can be used to access content tagged with a certain keyword. Sometimes they use more for classification and some do have metadata but most of them don't they don't have definitions or they don't have scope notes. And the other thing that taxonomies help with is faceted searches so you can really kind of dig down into data if you have a more standardized structure. So taxonomies and keyword tagging are really useful in IKM and potentially really powerful for linking content suggesting related content and supporting a deeper understanding. However, platforms and websites typically use that own separate vocabulary and taxonomy and these taxonomies are not connected and they only usually work within a platform or a website. They often use different variations of terms the synonyms we've talked about and few of these taxonomies contain metadata that incorporates definitions and scope notes as I've said. So one way of overcoming these challenges that face IKM and meeting user needs that we've heard time and again, especially over the course of the placard project and through our we adapt experiences to is the development and widespread use of a shared taxonomy for tagging content online. And this would incorporate all the terms currently being used but also include details of related terms that can be used to suggest content and provide the metadata to support and even deeper understanding and even an understanding for people who knew to this subject area who maybe don't know that there is related content that they could be looking at with with an initial search that they do. So one example of the development and widespread use of such a taxonomy is a search and discovery tool that we've developed in placard called the connectivity hub. Some of you may have seen this so I'll just go over it quite quickly. But the hub has basically been designed to enhance the search and discovery of existing information online. So it currently connects to five platforms, five adaptation DRR platforms, and it tries to connect this fragment of knowledge across the networks and across the knowledge domain. So this is a screenshot of the hub. The URL is there if you want to visit it. It's live now. And there's also a video there that gives you a quick walk through how to use it and why why it could be useful for your work. So the hub is really there to support several of the challenges that we've talked about. One of them is harmonizing terminology across the two domains. The other is to support coordination, collaboration and learning as part of the placard remit. And this is all done through keyword tagging based on the taxonomies of these different platforms and their use of metadata. So for example, if you were to click on a keyword here, the orange node here is the keyword and it shows the landscape of data associated with this keyword. The blue circles are articles and reports and the green circles are organizations. So if you were to use the filter on the, on the left hand side to just look at the organizations connected to this keyword. You would be able to see which organizations are working on this particular topic area. And similarly to try and support the understanding of terminology and language that we've just described earlier. If you were to click on a keyword, it would provide a definition of what that keyword means and to go into a bit more detail. I'll just quickly show you that if you were to click on nature based solutions. For example, you would be presented with the things that we saw in the pool party back end. So you would see the synonym, the alternative label, and you'd also see the related content. So have you also considered EBA have you also considered ecosystem services and you can flick them through, click them through into the different knowledge landscapes of these related terms. So you have a lot more flexibility just because there's a bit of standardization in the system. You have scope notes here too. And you have a glossary as you would find on nature Wikipedia or whatever. So if you hover over a term, you find further definitions. And if you were to click on to some of these source items, you would get to the source of where that terminology is arising from. So as mentioned before, currently platforms and websites approach keyword tagging in different ways. Some are dynamic and but many of them are not. And in order to create the connectivity hub, we actually had to do a lot of work to connect all the keywords. So to sort of understand what was what was synonyms or what we're matching terms across platforms, but they were using terms differently. We had to do a lot of that work manually because that standardization doesn't exist. But there are content tagging systems that make it possible to implement taxonomies for keyword tagging in dynamic ways. And one example of this is the climate tagger. So we've been working with our partners read who developed the climate tagger through pool party, which is developed by the semantic web company for a number of years. And I'm really happy to say we have our colleague Denise reaches here from climate tagger who can tell us a little bit more about that. Can I hand over to you Denise. Unfortunately, so I've just been talking to Denise. And she's having technical issues so she can't join us today, but we can say a few words about the climate tagger. So the moment climate tag is available in six languages and it does sound through Denise online. Sorry. Okay, well, I think we'll come back to Denise if she's if she's dropped off and Hopefully she'll be able to give us a bit of background into climate tagger in which case I'll hand over to Julia and she can take us through a bit more detail on the roadmap and what taxonomies can help us to achieve if we were to implement them. Great. Thank you. So can I just check that people can hear me. I'm not sure if they could. Yeah, we can hear you Julia. Thank you very much and you. So apologies for that. Unfortunately, Denise is having some technical issues, but we can say a little bit about the climate tagger as as I was saying before it's available in six languages, which it does through related terms. And one of the really powerful things we use it for and we adapt is suggesting tags so it can auto tag to some extent obviously this needs to be supervised, but does this using text analytics based on taxonomy. So this is just an example of how we can use these technologies to support a degree of standardization, but also helping to, you know, auto tag content which when so many of us have so much content online. I think we adapt we have two and over two and a half thousand items of content. So doing that retrospectively is a huge task. So there are these technologies that can facilitate these things and that's what we wanted to show there. But if you go to the climate tagger website, which I think we'll put in the Google doc, it provides a lot more information there. So I just wanted to talk about where this leads to so the connectivity hub is an example of what can be achieved with the widespread adoption of a shared taxonomy for tagging content online. And the climate tagger is an example of how such a taxonomy can be implemented and how this technology can support this kind of standardization. So this is a really powerful way of connecting content and promoting understanding so we can connect and find related content. It also enables us to analyze the climate action landscape. We can see, you know, how much content is coming up with a certain tag, you know, where new tags are merging and how things are evolving, maybe things are starting to bridge across multiple tags. And that's quite interesting in terms of seeing how things get evolving and particularly under the different frameworks. And when we combine this with APIs, so these are application programming interfaces, this better enables us to content share between platforms because we can do that according to certain tags so we're pulling the relevant information through. And as Sakena showed metadata is so important for supporting understanding and learning. So this is something we really want to push and see how being used so much more. But obviously to use a shared taxonomy effectively does require some standards for implementation. We need consistency in how everyone's using it. We need protocols and governance for how it's updated and how it's evolved over time. So this is just a link to the roadmap that, you know, those are things that we've really thought about and tried to build in there. But what I also want to talk about from a bigger picture perspective is how this contributes to the bigger picture and transformed IKM. So, there we go. Sorry, slides can be a little bit slow. So the widespread adoption of a shared taxonomy in a way comprises the steps towards linked data. So taxonomies and keyword tagging help us link data but it's not yet linked data. And linked data is the idea of linking all relevant content across the web to provide a global interrelated database, a web of data or some call this the semantic web. And this is hugely powerful for ensuring people can find the information they need as Tim Berners-Lee puts it with linked data when you have some of it, you can find other related data. But this does require the publication of data in common standard formats to ensure that they're machine readable and accessible to different machines. And so this is something that we're hoping to use a roadmap to help us achieve together. And if you want to know more about linked data, there's some links here and we'll share these slides after the presentation. But one key thing I want to note here is if we all publish our glossaries for psorio taxonomies, according to these standards we can better utilise and interrelate this data. So for example, just showing that the back end and pull part again, this is just a very simple link to the DDPDA linked open data set. So this is all the data on Wikipedia that's been made available in RDF format, which is a common format that enables sharing. So we can start to really link and utilise and cross fertilise a lot of our work if we do this. So that's kind of why it's one of the big features in the roadmap. On a related note, the widespread adoption of these taxonomies and moving together in these directions also comprises a step towards fair data. So fair data is data that is findable, accessible, interoperable and reusable. A lot of us will be very familiar with this kind of framing. But again, these require us to really think about standards and how we collaborate on the development of an adoption of standards to ensure we publish data in ways that conform to those principles. And say there's some links there as well, if you want to find more information on that, if it's not something you're already familiar with. So Taxonomy provides a foundation for powerful information knowledge management. This is already a big step forward. Spaces for keyword tagging to link related content, metadata for supporting understanding, related terms for suggesting content. Ontologies are an additional layer on top of that. They add the semantic information that provides additional contextual knowledge. And this is really powerful for supporting smarter infrastructure down the line. So with ontologies, we can attribute characteristics to term. So for example, we can designate certain methods as participatory. We can classify terms as a particular type of entity. So we can say, you know, this is a decision support method. This is a policy framework. And we can just describe relationships between these terms. So we can say, for example, that community based adaptation promotes sustainable livelihoods. And this additional expressiveness makes for much more powerful information knowledge management approaches. They allow for multiple relationships. They allow us to derive tacit and implicit knowledge regarding how terms are used and applied and make this explicit for machines. And this enables machines to think more about more in a way that we think that provides this contextual knowledge. And this can lead later foundation for smarter decision support tools and more intelligent content recommendation because you have that additional semantic knowledge about how those terms relate. So systems can be much more clever in the way they connect users with the knowledge that they think they need. And perhaps connect them with knowledge that they didn't realize they need, but the machine recognizes that they do based on these relations. So going back to the roadmap, and this is why we think it's really important that we have a common ontology framework for adding this semantic information that outlines these classifications and the relationships that are most needed to support users and power these tools. I just want to say a brief word on how this takes us to next level with knowledge graphs. So knowledge graphs are where we think the future lives. And together taxonomies and ontologies provide a detailed model of all the content in the subject area. This is the foundation of a knowledge graph. So this idea of having a roadmap that we kind of developed shared taxonomies, have a common ontology framework and then start to implement that helps us build a kind of a climate action knowledge graph. And in a nutshell knowledge graphs can be included as a network of all kinds of things relevant to a subject domain. So describes objects of interest a character that attributes and the relationships between them and that is really important for, you know, querying the system to understand how things relate to each other. And that provides us a much more powerful search capability. It provides numerous taxonomies ontologies and other knowledge organization systems, and so they can connect and bridge across multiple disparate sources of data. And they also, as I said, make it possible to make a very complex queries across all kinds of content and heterogeneous data sources and do this quickly. And this enables us to break up these existing data silos and connect data in smarter more meaningful ways. And a book that I found really useful is this knowledge graph cookbook which is a link there so recommend if anyone's interested in this they have a look at that. This is just an example of a very basic knowledge graph just to show this in context and you can see how you've got these different objects and this is explaining how they link to each other. And if you can think how a decision support tool might be able to leverage this. I think this is a really powerful step forward for using ICM to really expedite climate action. Knowledge graphs for those that aren't so aware of this area they are everywhere so the way Alexa Siri Google connect us to knowledge. This is all powered by knowledge graphs in the back end. And they can also, they're also really powerful for enabling AI applications because they provide the holistic sophisticated view of knowledge domains with all that contextual knowledge about how things relate and interlink to each other. This enables machines to make connections that are intuitive to us. And this can support all sorts of innovative approaches to integrating communicating knowledge that support this collaboration learning that's so desperately needed to achieve the goals under the Paris agreement and other international genders. And also support dynamic responsive knowledge systems, which is a key use need that we keep seeing coming up and up again, and also new levels of data analysis they make it possible to very quickly analysis. Huge data sets. So this is really cool. We don't have so much time to talk about this here but we are having another webinar on the first of July that will specifically focus on how the climate action knowledge graph that we can develop through this roadmap could be applied to really power these artificial intelligence approaches and how this can really help us expedite climate action. So to the roadmap. So hopefully people have had a chance to look at the report. So the roadmap comprises six concrete steps that we can all think about doing now some of us are already doing a lot of those. And then 16 steps in the medium and long terms that help us bring all of this work together. So the overview of that as you can see in this figure is that this involves a collaborative developments and linking taxonomies and common ontology framework by various actors so this is really inclusive collaborative approach. And one that is informed by experts and really focuses on meeting use of needs. And then another step is the integration and integration of these taxonomies and the use of the ontologies to produce the knowledge graph. I just want to say a quick word about the ideas behind it with this we really wanted to provide a collaborative pragmatic process that people can join in at different stages and progress at different speeds recognizing that some communities will be interested but we all have different capacities when it comes to contributing to such a process. And then there's also contributions at different scales. So this might be a very focused topic area might be a broad topic area. When it really recognizes makes use of all the work to date and there is lots of taxonomies and ontologies already available that need to be incorporated and built on and shared and interrelated and used and one that's achievable. This is definitely achievable. There's a lot of collaboration. It requires some leadership and we can come back to that later. But it is building on and making use of existing standards protocols technologies and thinking. So we can do this. And at its core as I keep saying is collaboration. Everyone uses terminology in different ways and we don't want to be too concrete about know you're right you're wrong. We're just finding a way forward that brings some clarity to the system so that we can really support non expert users and people really wanting to access this knowledge to be able to use it and apply it. So, just to go into the detail and apologize this is a bit dry with all the text we haven't yet thought about a better way of going through this. And say, in its whole is 16 steps. And the idea is that it's a very shared efforts so we have steps are led by active groups, these might be specific communities for example those working on the ecosystem based adaptation approaches. The next steps to address as a wider community for example the whole of climate change adaptation or perhaps even broader still. And those are undertaken by combination of the two. And although we present as a linear process. It's not in terms of numbering it's not actually a linear process these activities can be undertaken in parallel. Sorry, it's always happened at the most inopportune moments, don't know. So just to look at the first few steps I say it really wants to build on existing works so the idea is we clayton evaluates what is already out there in these different focus topics. We look at all the different data knowledge and information that is out there that will need to be described by these systems by these technologies and they'll need to be related by them. We really want to connect we want to be very used informed so conducting interviews and holding workshops of stakeholders to understand what content they use what technologies they use what their needs are in terms of accessing information and knowledge and how they want to do that. It's really important to hone in on the design of the icon systems and how we want to integrate this knowledge, which will inform how the taxonomy and the ontology is a structured and to share and discuss and use these outputs of course these multiple steps that kind of reflect back on earlier steps to say how do we move forward in the best way possible. And on the back of these conversations of unit users and understanding where we are as communities, we can start to think about prioritized icon activities that we can start to meet with these taxonomies as a group. We can then think about standards for how we manage quality assurance this is a huge topic. We need to make sure that everything is of sufficient quality that users can know that it's legitimate and credible. Also for recommending what metadata we use how we govern and govern taxonomies ontology and the resulting knowledge graph. And this includes decisions about licensing and publishing. And of course, yeah, so there's these talk about more standards and governance and these keep coming back so this is very much a phase approach of trying to cover these different stages. The common ontology framework really tries to build kind of, well just that a common ontology you know what relationships between terms do we need to provide what categorization is really needed to really provide powerful icon systems that can really bring the right content to people or manage it so that machines can leverage this in applications to provide these dynamic pathways through knowledge that are of the most used to users. And also this talks about developing and enriching you know this is not a one off effort taxonomies and ontologies will evolve through time just as a terminology we use evolves through time and the frameworks that we work under evolve through time. So there is this iterative nature that we need to keep revisiting keep expanding and keep working with subject experts to enrich these, these taxonomies and ontologies and make sure they are up to date and powerful as they can be. And of course, the main endpoint and this can be an issue throughout the process is really analyzing those overlaps and keeping connecting across these taxonomies, so that we have this integrated system where we can really start to connect all of this information across these disparate communities across these silos. And that is really the end goal of this roadmap is to really provide that high level of connectivity with the metadata that really supports users to understand it with that semantic makes it really powerful to apply to new ICANN or new innovative ICANN approaches, whether they be decisions, portals, knowledge management systems, and then we'll see artificial intelligence approach as our applications are a part of that as well. So it's kind of idea of moving towards smart systems. So it meant multiple things we think we can be doing now. And obviously, as I said, a lot of people are doing these things so obviously we have good practice principles and standards it'd be great if we could share more knowledge about that and come see what different communities are doing and what we can learn from each other. Same goes for existing taxonomies and ontologies. You know, we've kind of come across quite a few and you hear others through word of mouth, it'd be great if we can share these more explicitly with each other, so that we all know what's available out there already. Also engaging experts to validate and improve them, a lot of us do this anyway, but this is a really important practice, making sure that these taxonomies are effective and suitable for purpose. And also adopting and implementing these technologies within websites to tag content is a huge step towards, you know, realising things like the Connectivity Hub and actually being able to relate data across these platforms, across these websites so that we don't have these silos in this fragmentation. APIs, I mentioned earlier, this is a huge part of interoperability and knowledge sharing between websites, which a lot of users are coming back to this fits with this idea of having a single entry point or fewer entry points, and then they can go back. They can be driven to those separate websites through those entry points. And one of the most important things I think with all of this, and that we can all maybe reinvigorate our efforts to do is promoting awareness of why ICAM is so important and how it can really support knowledge uptake, how it can help expedite action. I think it's still a very underappreciated activity. It's kind of, you know, we want to put stuff online and as long as it's online and looks pretty, it doesn't matter so much. But there's so much good information out there that is not being used because people just can't find it, but I can't find it quickly enough. So this is a huge problem. I think, you know, we really need to drive that awareness and get that buy-in from leadership that can get the investment needed, which brings us to this slide. And so what we think is really needed to get this process going. So as I said, the awareness, the leadership to really drive these kind of agendas, the investment to build capacity and literacy for ICAM as well. And we've been on a very steep learning curve with this. I know we've got much more experienced people online today and I look forward to hearing from them. And then it comes back to this collaboration as well. And this is kind of a shift in thinking about how we approach ICAM. It's approaching it as a much bigger community collaborating and linking across our data sets, rather than having our individual silos. And I really hope that that is something that people share and want to pursue. And obviously, as I said, standards and governance, not the most exciting but so needed. So on that note, I know we've got Kristin on the line and I'm really glad you managed to join us. So Agrabok is an example of how people have come together and done this really successfully. And it's a big, a very large, extensive taxonomy ontology that is developed collaboratively. So Kristin, could I invite you to say a few words about this? I'll mute myself. That would help. Great. Thank you so much for joining us. Good afternoon, everyone. Emma was also here earlier. She's the Agrabok manager. We're running the EGOT meetings this week. So she had to go. She apologizes for that. But yes, hello from Agrabok. And we're so glad to have connected with the Black Card project at the end. Oh, it looks like a really interesting process. And yes, Agrabok is a large controlled vocabulary. And Phasaurus, it has about 37,000 concepts in about up to 38 languages, about 750 terms. So it's a very large linked open data set built for the voluntary network of editors that contribute to terms and concepts. So we have exactly the same, some of the same issues that you have when it comes to agreeing on terminology, making sure we have the right and current terminology. And that we remain relevant and agile, because this used to be very much used to tag documents, but increasingly it's being used to tag data sets. And exactly as Julia mentioned, in the age of big data, we need to be able to link and find the data. And just because it's online doesn't mean that people find it or that's accessible or usable. So, yeah, just nice to be here and congratulations on your work. And we absolutely think you're doing a nice pragmatic approach when it comes to agreeing on taxonomies, sharing it, building expertise, listening to experts to validate it. And that there also is very much a business case for doing this. Fantastic. Thank you so much. It's great to have you here and it was great to speak to you and Emma. Last week, I completely understand and not be able to stay on with so busy with virtual meetings now I think everyone so it's just great that you join a tour. Thank you so much. This is many questions. So, Kana, did you want to maybe start discussion? I'm going to leave it on that slide. We can go to the Google doc, perhaps. Yes, so basically, this is really an opportunity for everyone to share some thoughts about what they've heard and and what as Julia and Kristen have said what what do you think is possible are there shared taxonomies and questions out there that perhaps we're not aware of that we, you know, we could be working together as a community to link better and connect better. And basically just to hear, I don't know if anyone has any thoughts that they'd like to share questions to ask you can also put them in the chat. And Andrew will help us field some of those questions. So we have a question, a comment from Faye from Waifo to connect to the ISO they've developed commonly agreed taxonomies for a long time. Yes. Yeah, this is something we are aware of and we do have colleagues working on those standards. So, yes, that's something we are looking into and we hope to take forward. Anybody else have any comments or questions advice. I think we have people who are a lot more knowledgeable about this stuff than us probably we are not computer scientists or taxonomists by any stretch of the imagination. And maybe we can say a little bit about how we're, you know, we have started building kind of generic taxonomies for CCA and DRR through merging a lot of the terms that come from those different platforms in the hub. And we're really looking at taking this work forward. So if there are people that are interested in collaborating I think there's sections under that Google Doc, please do drop your name and the email address under that and, you know, we'll try and keep in touch. As this work progresses, let's say placard is coming to an end it finishes at the end of this month it's been a great few, well, I think, five years for CCA and a few less for me. But we are working with key partners to take this forward. So it would be good to kind of get a bit of a community going on this. Yeah. Thanks, Julia. I just dropped another link in the document that takes you directly to another page in that Google Docs so there are different ways to engage with us and with the wider community. There's a few options there in terms of if you're interested in the hub and helping us test and evaluate the hub. Please add your name to that document if you're interested in exploring more what's possible with taxonomies and new collaborations and projects around developing taxonomies, please add your name there. There's a few different options there and if you think of other ways to engage and maybe you're doing things that are relevant and related. Please add any details there. We have a question here about whether there are any thoughts on having an international convention to agree on terms, which is a really good question and kind of goes back to the leadership point that Julia was making. So I think this is where we kind of want to raise awareness about the value of this type of work and have some consensus on the need for that. So in different communities, there is already quite a, I mean, for example, UNDRR has its open-ended, international open-ended expert working group on terminology, I think it's called, who have been developing and standardizing terms on DRR for a long time, but again, we don't have the same on the adaptation side. We have glossaries developed in the IPCC reports and they're not published in a standardized format that we could automatically use, for example, in the hub. This is one of the obstacles we came across in developing the hub and then within the platforms where we've incorporated terms from across the five platforms in the hub, for example, different platforms are using different tagging systems or some are actually just using expert-driven processes. So they're very valuable terms and very good terms and they're coming from experts, but they're not classified in a formal way. So we have this real tension between having a lot of good quality information out there, but it's not shared in a way that we can reuse it or that's easily, hopefully, that answers your question. Hopefully my mic is still working. Did you want to follow up on that, Juan? I see you've got your video on. It's good to see you. Hi, Juan. Should I talk? We can hear you now, yeah. Well, that sounds interesting. I was just thinking on another. Well, I think all of these brings a lot of questions. The first one I, or the first two I think is this calls maybe for what some people call like gatekeepers maybe like I think there's a lot of need of people specializing on only managing these kind of systems and keeping them alive. I don't know where funding for that will come from. So that's kind of my first question. And the second thing that I was thinking is looking at the last example you showed from FAO. And most of the information you are looking at or the taxonomies are in English, but FAO showed they have it in different languages. How much are you thinking about including things in other languages? For example, I'm from Colombia, so it will be interesting to also kind of see things in Spanish, which is, it's another of the languages I use, perhaps in my work. Absolutely. It's great to have you join us. And it's quite early in the morning. Yes, as I mentioned, I'm one of our key partners is REAP who developed the climate tagger. They developed that is available in six languages. And that's definitely, I think the aspiration is like whatever is developed is translated with experts into other languages. And of course it has to be done with experts because literal translations don't always make sense. So that is definitely something we want to do. Who say it's getting funding and leadership to do this, I think as part of Placard, we were looking to institutionalize a lot of these approaches, there are still discussions ongoing on that. And I think it's really exciting for trying to pull these together and to start the grassroots, really bringing people together to really talk about IKM and how people are doing it. Because even between the platforms that we work with and that our colleagues of ours, there's not a lot of knowledge sharing on anything, let alone this specifically. There are some projects that are underway now, but this is still kind of a growing process. So I guess it's watched the space, we're doing our best and if anyone wants to join us, please drop your email and it would be very glad to keep in touch with you. And did anyone else have any questions or thoughts or comments? By all means, if you don't want to ask to the room, you can pop it in the chat or if you have reflections later, I say our details, we can put our details in the Google Doc. If anyone wants to get in touch with us, if you have a strike of inspiration or have a burning question, say tomorrow, we can get in touch and take these things forward. Hi, if I can just jump in. First of all, thank you. Thank you very much for this presentation. My name is Rodrigo Jimenez and I'm working for the GIZ in a project called the NDC cluster. And we are now dealing with knowledge management and information and this is very helpful, of course, also to understand from the basics of what is actually the terms that we all need to have in mind and have in common. And also very useful to know what is there out there already. And yeah, basically, I will look forward to the content and the Google Docs and also the presentation to perhaps have a closer look and their contact details as well. Thank you. Thanks so much. Thanks so much, Rodrigo. I also just wanted to mention that. It's interesting that you mentioned the NDC work that you're doing. We, in the report that we've just published, you might find it useful to see there's a few case studies in the report, which show how taxonomies and terminologies have been used to better organize and classify information for making between the NDCs and the SDGs, for example, and for other work around the SDGs around the European green finance taxonomy. And so there's the World Bank. There's a nice example from the World Bank as well. So there's lots of practical applications that we've tried to highlight in the report that might shed some light on how taxonomies can be useful for different areas of our work. So I would be happy to hear from you as well if you want to get in touch. Thank you. We had a raised hand from Kristen a few moments ago. We had a, again, just to say I really wanted to applaud the idea of looking at a things like ISO and just just agreeing on authorities you would use for concepts and definitions is a big step for community and not always simple. Because there isn't always an agreement, an international convention, that would be nice. But as you say there are known authorities already working on disaster risk reduction, for example. And that means you're going to find collection control vocabularies, translations, definitions, both that you might use, but also might benefit from your expertise. And ones like AgriVoc, we're certainly very happy to hear about things we might be missing and to benefit from your wisdom and your collections. We also have a lot of material in Spanish. You're very welcome to use that. So just a good luck with the work. It's really important. Okay, thank you very much, Kristen. May I ask something else? Yes, please. Just to be clear, what is kind of the nature of the collaboration that you're looking for? Is it going to be on a voluntary basis? Or are you going to have a job positions, more formal job positions for collaboration? And how is it going to work? Or what are the kinds of ways to engage in this kind of very interesting project? So I think one of the things that's really open right that that's one of the things that's really open right now. So with with the placard project ending. But with a lot of interest and new avenues opening up for the kind of work and challenges that we've been trying to address. There's still so much to do. And so we were basically hoping to find opportunities to work with others to take this forward. One of the things will be to hopefully try and scale up the connectivity hub and increase its reach and visibility, the visibility of the content in there, increase the amount of content in there and the way that it can support the use of a shared taxonomy. And that kind of is a test bed for lots of these technologies that Julia's been describing in terms of, you know, better developed taxonomies, working towards ontologies and knowledge graphs. So, we really see this as a fantastic opportunity to accelerate progress towards the goals that we're trying to achieve in our work. And we actually just trying to explore what's possible and find out what others are doing as well. You know, connecting with Kristen and I meant Agrabok has been great. There's a lot of work that we were not aware of that we found while we were doing the research for the roadmap. And so, yeah, it's pretty open really I mean we're looking for ways to engage on new projects. There's lots of new proposals that we would like to write for this work. So we'd be happy to collaborate on any of those things. And language experts are always going to be high in demand, I think, because we do want to move in that direction. We do recognize that not everything in English and these kind of technologies are actually also very useful for linking content in different languages and helping a translation as well. Definitely. We've got a couple of minutes left. So if anyone has any questions, please ask them now. Do you want to keep to the hour because we realize everyone's got busy schedules. I just wanted to just re-share, sorry, where is everything? There we go. The webinar that we'll be hosting with our partners who we mentioned, so that's Reeve and the Semantic Web Company who we work a lot with. And they are the ones who host the cool party software that we've been using. Obviously there is other software, but it's one that we found very useful and they have been great partners. So that will be a much more technical webinar. So we're really exploring how knowledge graphs, which is the end goal of the roadmap, can be used to leverage these artificial intelligence approaches. And so as most people on the report on the call will know, AI, it's just it presents massive opportunities, a massive potential of who care needs to be taken. It's just an exciting field. So if for those that are interested, I do hope we'll see you there as well. So that was on 1st of July. Again, in the evening, so it'll be a slightly later time of five o'clock in Central Europeans. So hopefully a slightly more acceptable hour for our colleagues joining from South America. And thank you again for joining. It's great to have people from across the world. It's such a global problem when we need global solutions. Yeah, and if I can finally just say that the Google Doc will be open for you to contribute to for the, at least the rest of this week and maybe early next week. So if you'd like to put some ideas in there about how you'd like to work together to try and address some of these issues or if you'd like to just stay involved. If you're willing to be a user to test the hub, for example, or if you're just want to stay informed about the latest updates, we'll be trying to put together a mailing list or have a discussion forum or something like that that we can as a way of staying connected and increasing conversation around this as well. Great. Thank you. And I think we'll be sharing a recording at the webinar and we'll share the slides at the same time. Yeah, probably by a dropbox or something because there's a lot of images. So that you have access to those links and we'll reshare the report in that as well, which has a lot more detail on the things we've been discussing is quite difficult to synthesize something that large and in just half an hour. So thank you again for joining. And yes, we will be in touch with those who want to take us forward. Thank you again.