 Okay, so I'm Jason, and I've been working as a wicamegian with the National Library of Wales for nearly three years now. For the first sort of two and a half years, that was as a wicamegian in residence, and then in the last few months they've appointed me as a permanent wicamegian, and my job title is now National Wicamegian. Thank you. Yeah, so initially my role was all about sharing images, encouraging people through events and workshops to contribute to Wikipedia in Welsh and in English. No one really told me from the start about wiki data, so I had no idea what it was or what it was for. I feel now like I've got a better grasp about what it is. I still really have no idea what it's for, and I think that's part of what attracted me to wiki data, is that for some people it's about structuring data, authority control, connecting different data sets together. For others it's simply an open repository, a way of sharing their data with a wider audience. So the potential reuses for wiki data are really endless, and I think that's what makes it so special. For me and for the National Library of Wales, wiki data currently is really for improving access to our data, for enriching our user experience, for collection discovery, and for connecting our data with the wider semantic web. After a few months of our residency I started hearing whispers about this wiki data thing and decided I needed to learn more. Then I went to a wiki data workshop in London, and I met some wiki data people for the first time, including Naveeno Evans, who's one of the co-founders of Hystropedia. Following the conversations that we had, I went back to Wales, generally excited and I said to managers, we need to start doing wiki data without really knowing what we were going to do. So since then we started embarking on these projects to share samples of our data with wiki data and then looking at what we could do with that, what were the advantages for the institution for doing that. So this talk really is about showing you some of the things that we've done with wiki data in a bid really to show you why Glam and wiki data are such a good fit. So before we even started contributing to wiki data we'd been sharing a lot of images openly with wiki commons. The reason I mention that is because I think it's important in order for Glam's to get the most out of wiki data that you have images that can be used to illustrate the data that you're describing, particularly if you're describing images. Incidentally releasing images or media openly with wiki commons is well proven to generate high impact. So we've had over 300 million views of our images through that impact, through sharing them in Wikipedia articles and that can be really handy when trying to get managers to sign off on more interesting things like wiki data. So obviously images aren't always going to be relevant depending on the type of data that you're putting into wiki data but in terms of visualising and encouraging creative reuse of data we found that having media attached can be very useful. And we actually believe that the National Library of Wales has more wiki data items about artworks with connected open images than any other institution in the world and that's something that we're quite proud of and we're hoping to build on this. We've got about 5,000 images in a Welsh Portrait Archive that we're hoping to share in the next few months and again we're looking to sort of put that into wiki commons and wiki data is a matter of course. So really the National Library of Wales has adopted this policy that anything that's in the public domain images we want to share the information as widely as possible. Commons allows us to do that with the images, wiki data is perfect for actually doing that with the data as well and that just sort of breaks down barriers for reuse and encourages more people to actually use that content. So the fun fact here, wiki data has got 23 items for artworks with images attached that depict the Coliseum which struck me as not many so I looked up something in Wales. Conwy Castle in North Wales has 160-8 items with the same criteria on wiki data. But to be fair to the Coliseum this is the second biggest castle in the whole of Wales so you know. So I suppose the next question is okay that's an interesting fact but why? What's the point in sharing all this data and what does the institution gain? So of course that's probably what your boss is going to ask as well when you say let's share all our data with wiki data. So for me the answer is simple it's really about giving added value to the collections and your open content. And if you're ever trying to convince Glam's to collaborate with wiki data or another wikimedia project it's always better to show them the benefits, to show them what they will gain because they're far more receptive to that generally than telling them it'll benefit open knowledge in general and open access. So in the case of the National Library there were some really obvious benefits and I'm going to show you some of those now. So if we look at our Welsh landscape collection which is one of the collections that we've released through wiki data this is how you'd have to search the collection in the National Library catalogue. It's all kind of bundled in with everything else in the collection. So in fact to actually search just within this collection you have to use an advanced search. And it's very limited in terms of what you can search for, you can search for the title, there's a few tags in the metadata that will pick out images. But you can see it displays the image sort of a window within a window which doesn't look particularly great. It's very limited metadata actually displays although there's very rich data for this collection it doesn't all fit in with our current catalogue which is like a generic library catalogue that's primarily designed for books. And there's no way that you can sort of dig deeper into this, you can't then display images, other images by the same artist or other images of the same place. So it's very limited in what it can actually do. So in order to add value to the collection we took this existing data that we've got and empowered it by converting it to wiki data. And the data that you see in this example is all data that we had it just wasn't being properly utilised. So there's currently no sort of handbook a sort of step-by-step guide on how you go about taking metadata and converting it to wiki data like this. So we kind of learnt as we went along because I'm not a wiki data expert I'm a muggle as John Cummings would say. So we sort of learnt as we went along and a lot of the praise in this case with this collection goes to our wiki data visiting scholar who we've worked with very closely and so he's a volunteer and he's done a lot of the work of actually matching up the metadata to wiki data. So what became really clear from quite early on in this process was that this was going to actually enrich our data. It was going to make it better. For example, one of the first things we discovered was that as you take place name tags from our metadata and match those with the places on wiki data, you get geolocation data which means we can display the collections on a map for the first time. And we also noticed that when you start structuring the data mistakes in the metadata become much more obvious and we can then work to fix those. So using the Sparkle query service it's possible to query the data in an endless number of ways making it very easy to uncover patterns and gather statistics from the data and then visualize them in a way that people can easily understand. So this visualisation depicts the most shows you the most depicted things within that Welsh landscape collection. So it's no surprise you've got things like ruins, mountains and rivers. It's all very Welsh. What you can't see there, there's actually 15 images that depict goats in the collection just as a random example. What's really great about this process for the National Library of Wales is that of course wiki data is multilingual. So we can describe the data in any language we like including Welsh. So here is the same query again and we've just flicked the switch to Welsh. And this stunned me the first time I saw it because I suddenly realised what we'd done because the data that we've got at the National Library for this collection is only in English. But by putting it into wiki data suddenly it's all in Welsh. We didn't translate any of these terms. This is down to volunteers over the years adding Welsh language labels to wiki data items. And virtually all the terms that we've used in this collection were already in Welsh on wiki data. There's over a million items with Welsh labels I believe. So for Glam's working in a bilingual or a multilingual environment wiki data can really help support access to data in whatever language you like. So then we looked at using third party services to see what we could do with the collection. So we used a website called Krotos to explore and filter our collections through wiki data. So the first thing you'll see with this interface is that you can visualise the data and the interface itself in dozens of different languages including Welsh. You can use the slider to search for images within a particular time frame. You can browse, you can ask it for random images from within a particular collection. And then you can click on an image, see the detailed link data for it so that you could then break the collection down and say, OK, I want to see all images by this artist or by this publisher and explore the collection in ways that you just can't on the National Library catalogue. So here we've searched for images that depict boats and you see you just get the images that depict boats. We can do the same for places. So this is Canaven Castle in North Wales. I think this is the biggest castle in Wales. And because of the quality of the data, we can even break it down and look at a particular tower, a particular part of that castle. Because of the work that the archivists did long ago, but their work was never being sort of utilised through the library catalogue. We've also, through this process, enriched the data for this collection with detailed information about the artist, the publishers, the engravers involved in the collection. And we've used third party authorities such as Veaf to do that. So we can, for example, see and break the images down based on the publications they were first published in. And then you can see here the engraver of that volume was a guy called John Boydell. If we want to know more about him, we can use the query service, various Wiki tools and we can look at his connections to other publishers and printers within the collection. So all these things that I'm showing you, they're all free tools that are available online. A lot of them are open source. They haven't cost a penny, whereas the National Library of Wales catalogue cost millions of pounds. So, if you remember that slide I showed you of the National Library of Wales catalogue, this can do so much more. So it really gives added value. And it's all down to volunteers, community engagement, and it generated a lot of community engagement. And of course, Wiki data is a platform. So for those who want to drill down into a collection or explore and analyse data, this goes way beyond what we can offer with our own website. And I don't know anyone in the glam sector in Wales, particularly budgets are falling, there's constant cuts. So I think low cost collaborative solutions to give added value within the library like this are going to become all the more important. So I've talked a bit about data for images, but Glam's, of course, could be using Wiki data to share all sorts of data, such as biographical data, or we've used it to share data about items from our archives, such as maps, in a bid to breathe new life into the data. See the link there. OK, so for example, we've got a dictionary of Welsh biography, and we've been looking at using that Wiki data for this. And what can this do for us? So here's the current dictionary of Welsh biography website. It's nice, isn't it? I'm sure you agree this would probably be better and more at home as part of the archive rather than a gateway to the archive. It's a little bit dated. So how can we add value to this kind of resource in a cost effective way? And for me, Wiki data is at least part of the solution. So again, when we went about creating Wiki data for the dictionary of Welsh biography, we engage volunteers. We initially in the mix and match process and then during the process of enriching the data. And this is actually a sort of Wiki data editathon hackathon that we did with staff at the National Library of Wales. So now that we've got data for individuals in the dictionary of Welsh biography, we can start to do cool things with it. For example, we can use this timeline to view the collection chronologically and we can filter it based on where people were born, where they died or in this case, on their occupation. And the images that you see here are some of them are images from the National Library of Wales. Some of them are images from other institutions and they're drawn in, of course, through Wikimedia Commons. So this again is giving added value to the service we provide. So this timeline is based on this trapedia and we're now looking at the National Library to collaborate with people that make this kind of software to help us make bespoke interfaces that we can integrate with our own websites to give added value to those websites. And we're pretty sure that sort of using this enriched data and working with people that are developing these kind of tools, it's going to be far more cost effective than trying to develop something that does something similar in-house. So until now, the dictionary of Welsh biography was basically tagged text files about each individual. But by turning that data into structured data, we can actually start to analyse that for the first time. So this chart gives you the life span of individuals that are covered in the dictionary of Welsh biography based on their occupation. So you probably can't see, but the lowest life expectancy is for missionaries. And the highest two are teachers and university lecturers. Interestingly, the after missionaries, the worst off are lawyers, which is an interesting one. So as we get more data in, perhaps we'll find out more if we get cause of death, for example, we might find a little more information about what happened to the lawyers. But as we improve this, we should be able to look at other things as well. It'll be really interesting to look at the dictionary of Welsh biography in geospatial terms, for example. So that's a few examples of the data that we've been sharing with Wiki data, but we've also shared other collections. We've been putting data about Victorian shipping into Wiki data, creating items about historical Welsh newspapers and journals, manuscripts and maps. And we've been collaborating with other institutions. For example, we just worked with Cadw, who were responsible for all the listed buildings in Wales. And we've got all 30,000 Welsh listed buildings now in Wiki data. So I hope I've highlighted some of the advantages of working with Wiki data to enrich and provide better access to individual data sets. But of course, the value goes way beyond that, because Wiki data is about connecting collections together. Both collections from within one institution, but also globally. The sum of all paintings project is a great example of connecting up collections from all around the world. So here's a quick example of how some of our collections have become entwined, and we found connections that we didn't know existed simply by using Wiki data. So I've taken the example of a mansion that's just a couple of miles down the road from where I live. So if we look at this on Wiki data, it's depicted in our Welsh landscape collection. It's also a grade one listed building tying into the listed buildings data that we've just released. There's also Reverend William Powell on Wiki data, who's part of the dictionary of Welsh biography and he's listed as an owner of the property. We've also got several things that are named after the mansion. So we've got a ship in the shipping records that is named after the mansion. And we've got this interesting little bowl here that's called the Nanteos Cup. And again, it's named after the mansion. It's now part of the collection at the National Library of Wales. So you can see all these different connections. And before I move on, actually, that cup is one of the few items on Wiki data that uses the instance of Holy Grail. So we've actually connected landscape prints, ships, people, and the Holy Grail. So these are things that we just had no idea that we could connect together until we started using Wiki data. So there we are. So what's next? What is next? So yeah, firstly, we want more people to be reusing this data that we've shared. We've started working with local universities to provide data to computer science students. So look, this is our Wiki data, go and do something cool with it. So we're hoping that's going to bring out some interesting results. We want to start holding hackathons and just getting as many people using our data as possible. We want to use the data, this enriched data in our own websites. For example, we're looking at bringing in the geolocation data from the Welsh Landscape Collection so that we can add those images to our Welsh Places website and view them on a map. We then want to go one step further and use Wiki data to actually power our websites so we could use the timelines, for example, or generate info boxes, or have maps that are part of our core websites, starting with a new Dictionary of Welsh Biography website that we're developing, hopefully, so that Wiki data is actually powering our services. Developing the Welsh language in a digital environment is actually a priority of the Welsh Government at the moment. So we've been working closely with them to try and get more Welsh labels into Wiki data and working with Welsh universities on machine translation technology. And that, in turn, should lead to better Wiki data integration on the Welsh Wikipedia. We saw the article Placeholder in the presentation this morning. That's something that we want to see develop on the Welsh Wikipedia. We've already got quite a lot of info boxes that are powered by Wiki data and lists and we're hoping that Wiki data will become more important, which is particularly with a small Wiki. It's a very good way of managing the accuracy of content sort of semi-automatically. So that's it, really. I hope I've sort of given you some good examples of why Wiki data and GLAM can be a really good fit. I think there's potential for us to do a lot more. So, yeah, happy birthday Wiki data and thank you for listening. Yes, no, yes. If you're interested in bringing content back into the collection from Wiki data, not just pushing it out or maybe embedding, how are you organizationally dealing with concerns about vandalism, concerns about content quality? It's no longer only our official information. These are things that GLAM and curators are naturally worried about, especially if we are live embedding information on a GLAM website from Wiki data. It introduces a new interesting vector for vandalism. It does and this is something we're only now really starting to debate seriously. One of the things that we're looking at doing is bringing data from Wiki data into our catalogue records to enrich it and give extra data. So we need to be clear whenever we do this that what you're providing is added value. It's not library data that it's very clear that it's come from an external source. But I think at the end of the day, if you get too worried about vandalism and just get too frightened off by the whole thing, it just won't happen. So, yeah. But just to add on that, I was wondering if part of the conversation could be also a technical one. So I know at Europeana because there is this concern of mixing curated data with other data. So in a way the technical means that came to our help was annotation. And so basically every time we link something to Wiki data, this is represented as an annotation on top of the curated data. So I wonder if there are other things like that that could join the discussion saying, well, there is limitation, of course, but there are also some technical means that can be used to help and also maybe leverage maybe lessen the concern of the curators, etc. I mean, it's part of a wider initiative, for example, that the National Library were developing a volunteer platform for transcribing and enriching data for our collections and that, too, we want to bring and be able to display through our catalogue. But again, that's user, that's volunteer created data. And so Wiki data that's brought back in may well sit with that kind of data as sort of added value data. It's just clearly defining the difference between the two really. Yeah, from a service point of view, I'm very much a fan of not directly linking live data to have to keep a local copy copy. So how do you think one should deal with update cycles in both directions? If you have established a connection then you would not necessarily always have human interaction, but have this automation and a refreshing process somehow automated. And I would really like to talk about this kind of tooling and connectors that we need between Wiki data and Europeana, for instance. Yeah, I mean, I think we definitely need these tools. I'm not a particularly technically minded person, so I wouldn't. I don't really know how you'd go about doing that, but it's definitely something that you need. And I think it would be really interesting to have more tools from the Wiki data and to be able to monitor items and check them against your data. And I think the thing that was mentioned this morning about institutions being able to sign off on statements that have come from their records in Wiki data, that kind of thing would be really useful in trying to make the items as accurate as possible and monitor them. Hi, Sean Angon. Thanks a lot for your contribution on Wiki data. We really enjoyed to see and to discover so many things about Welsh. It's really great. And one key point of your contribution is the high quality of metadata, which is very, very good, especially for depict, as you explain it. And we have many, many depict on the artworks. And I wanted to know how did you produce them? Did you make matching before or along the way of the contribution? So I would like to know how do you do that? Okay, so with the bigger collections, like the Welsh landscape collection, the images had been tagged at the cataloging sort of archiving process with tags describing what appeared in the images. And so we literally just converted those and mapped them to properties on Wiki data. With some of the smaller collections we've worked on and we've run some volunteer projects where we will manually collect that data and add it during the process of preparing all the data and getting it into Wiki data. But I think it's really important if you're going to put artworks into Wiki data that they're well described. I just think the possibilities in terms of reuse are so much greater if you do that and it's worth investing the time to do it. Go for it. Again, if there's no one else, what is the difference between or can you explain the role of national Wikimedian in the sense of you're working with an individual institution. Do they mind if you are doing projects that don't have a direct relationship to that institution's collection? No, they don't particularly. That's rare and exciting. That's usually a problem of Wikipedians in residence if they find someone wants to do something really cool but it doesn't have a direct benefit for the institution. The way that we've tried to set it up and frame it and make it look attractive to the National Library is that they're establishing themselves as an umbrella organisation that can help other organisations in Wales to share their content openly, to understand open licensing and link data and all these kinds of things which puts the library in a stronger position in terms of funding, for example. Also a lot of the work that I do that isn't directly related to the library are funded or at least part funded from external grants and that brings more money into the library and it creates partnerships through working with getting the listed buildings data. We've created a partnership there and a two-way conversation with an institution that we didn't have much contact with otherwise so it helps the library build up those networks. Thank you. No last question. Thank you.