Hello everyone, nice to meet you. My name is Sandra Fukunye and I am a long-term Wikimedian and I currently work with Operefine. I will give you a tutorial of Wikimedia Commons uploading with Operefine. Here's a few slides. In this session, we will actually start with a recorded demonstration. I am doing that because I am a little bit hesitant to do a live demo. You always know that these things tend to go wrong sometimes. So there's a pre-recorded demonstration, but I am around and the demo will be shorter than the session. So whenever you have questions while you see me do things, please ask your questions. I would say either in the chat, but it would even be better if you ask the questions in the sessions either bad. We have an either bad for the session and you can place your questions there. Then in that case, if you do that, I can see your questions, certainly. After the demo, we will answer those. Maybe some of your questions will already be answered while I was giving the demo, but the ones that remain, I will be available to answer them. Let me start by giving a very brief introduction for those who don't know Operefine yet. Operefine is software free open source software that is used actually quite widely. It's quite popular software used for data wrangling for working with large data sets, data operations, modifying data, and preparing to upload data to other databases. So sometimes jokingly call it spreadsheets or Excel on steroids. It basically is a little bit like Excel in the sense that you see in the screenshot here you see the data in a grid view.  It runs as a desktop application.  It is a little bit funny though because it will not run as a native application but it will open a tab in your web browser and you will work with Operefine in your web browser. You will see me do that pretty soon. So I already said to Operefine is quite widely used. It is widely used, not just by Wikimediants. It has been used by Wikimediants for a while. But it's software that has been around for more than 10 years now and it is used in the cultural sector by museums, culture institutions, libraries, a lot by libraries actually they are our main user group. There are also data scientists, journalists who work with lots of data by activists around the world. We also our interface is also international. We have translations of our interface in languages like French but also Japanese, Indonesian languages etc. So since several years you can use Operefine for batch editing Wikidata so you can use it to do data imports and to Wikidata. And in the last year we have also worked on a project to extend Operefine with functionalities for Wikimedia Commons. And that is what I'm going to show you in this session with a focus on uploading new files to Wikimedia Commons. And that is brand new. Oh, just to reinforce that Operefine is actually indeed a widely used software. This is something I really like. This is a t-shirt that an Operefine fan has made and the t-shirt says Operefine is magic. So I recommend actually Wikimedians who are interested in working with cultural institutions to work, learn to work with Operefine because it is software that is really popular in the cultural sector. So it will help you with your work in general. But so going back to Wikimedia Commons support, we have been, as I said, we have been working on Wikimedia Commons support for a year now. And at this point in time you can already do batch editing existing files of Wikimedia Commons with Operefine and file uploads, which I'm going to demo now. The focus is structured data though. So you can do Wikitext editing with Operefine, but we really, really emphasize using structured data. It is a tool that is focused on structured data. So it has been used for Wikidata and now we also use it for structured data on Wikimedia Commons. In terms of difficulty of how to learn to use the tool, it is actually, we see it as the replacement for the Glambiki toolset. The Glambiki toolset was an advanced tool that was easy to use by or not easy to use but was really powerful for cultural institutions who would do exports from their database and then import files into Wikimedia Commons. We see Operefine as a replacement for that, but it's way easier to use than the Glambiki toolset. I would say in terms of difficulty, it is somewhere maybe in the middle between PatiPen and the Glambiki toolset. And unlike PatiPen, Operefine as I said supports structured data. So that is a big advantage. You can add structured data from the start and it is a tool that cultural institutions already use. So your partners might already be familiar with it and it will help you in your partnerships. By the way, we are doing this project thanks to a grant from the Wikimedia Foundation for which I thank them. The project runs until the end of October 2022. So after this session, the demo that you are getting now is not the final software, we will still add some user friendly features. And actually, I got a good news that after October, we will also have a budget, not so much for new development, but for bug fixes. So we will be able to do that. And we will also have a budget for training in the Wikimedia movement. So this session is definitely not the only one that you will see, but I will look into various ways of helping Wikimedians use Operefine better. So this session is by the way going too fast for you, which I totally get. There is already some documentation on Wikimedia Commons about batch editing and batch uploading. So we have an info page on Wikimedia Commons, which you can consult. And that one, we already have 12,000 uploads, which is great. And there you find a link to how you can add structured data with Operefine. And there is also a Google document with instructions on how to upload files with the current features. This is not the final documentation because we will still improve our features. And I will put of course final documentation on Wiki and in places where the Wikimedia community can use them better. So demo time, I will actually start demonstrating how very quickly how you do batch uploading to Wikimedia Commons with Operefine. In the course of this session, I can absolutely not show all the features. We have too little time for that. I think to learn to use Operefine well, I would say take an hour or two. Then you can learn the features of the software itself and you can also learn to do the Wikimedia things with it. In this session, I will really focus on uploading new files. So I will actually not go too much in depth into all the very powerful things in general that Operefine can do. But as I said, later in the year, we will start on training and that is also something I really want to cover learning to use Operefine in general. By the way, on the Internet, there are many, many tutorials that are actually quite great for that too. So it is not the first time that people are learning to use Operefine. So, but yes, for this demonstration, I am going to show you how to upload a set of files. I have chosen a very small set of files on my computer right here. Like most Wikimedians in the world, I go around, I see the world and I take pictures and then I have many, many pictures on my computer that I've taken myself of interesting things in the world and I have not uploaded them to comments yet. And I thought Sandra, for the demo at Wikimedia, let's fix some pictures you took in 2020. So I have around nine pictures of a really big structure around my hometown Rotterdam. This is the Rosenberg Windwall. And I also have some pictures of a public artwork in Belgium. This artwork is called, I wrote it down. It's French, well it has a French name. Le Val souffle ou eu vu from the artist called Daniel Buren that is on the Belgian coast. And I will show you how I would go about uploading these files. So first, of course I have these files on my computer and I am going to get their file paths, their local file paths. This is something that we hope to improve with the feature. So that you don't have to do this step anymore. But basically I'm now going to get a list of file pads. I'm going to put it on my Mac here. I'm going to copy the file pads here. And I am going to open refining my browser now I have started open refining my computer and open refining this open here. And I now have on my clipboard on my computer clipboard, the list of file names. And as you can see here, this is the start screen of open refine and you can start using open refine with many different starting points like a file on your computer. And then you can address something like an API over over cultural institution cultural institutions will be super happy with that. That they can just feed you know, a link from their API in here and then open refine will load the data. You can also do an external database I've never done that in my life but it's possible. You can do Google data sheets, or Google spreadsheets. I also are building an extension to start from Wikimedia Commons categories to edit these files. I have not edited that extension for this demo. But in this case, I have file pads on my clipboard, and I will paste those here. So, what you see here is just a link of paths of where I have. I think around 1516 images that I just show you. And this looks good to me. I'm just going to start a project with that. So what you see here is a preview screen. And I am going to tweak some things that now it interprets that I actually have a column name with users and then my user name and desktop. That's not what we want. Let me see. Yeah, this is what I want. I just want one column with my file pads. Just a side note, it is totally fine to start in this way with just file names from your computer. But you can also start with a full spreadsheet, right, or a full database that maybe you have file pads somewhere. And you already have the data about these files somewhere on your computer, somewhere in a data set that is also good. I will actually add them as I go, but this is one way to do it, but you can also have more data to start with. All of that is, by the way, explained also in this Google doc. So I'm going to start just here with file pads. I forgot to say, I am now uploading files from local files on my computer here, but you can also upload from URL. So if you have a cultural institution that has, you know, you are partnering with a cultural institution that has files on the internet that has files on the web of their collections. So you can actually also use these links to upload directly from that so you don't have to download them to your computer. I'm now going to give this project name. It's a little bit like creating a file. I'm going to say demo wiki mania 2022. And I'm just going to give it some tags. If you work with opera fine all the time, you will have a lot of projects going on in your opera fine software, and you can use tags to make them discoverable demo. Why not upload comments. There we go. I will create a project and it loads. And here we are. All right. So we have this list of files on my computer here. It actually says that we have 16 rows, but we only see 10 open refine has a way to limit the few of the data that you have that is also a thing that is featured to also preserve memory or to be more careful with the memory of your computer. If you are using really big data sets. You can have use of fewer data like 50 rows at a time. I will now switch to 25 rows. And I have a column of files here. Now, of course, I want to have some extra information about these files. So in the next steps. And I'm going to skip through that in the recording a little bit. I will actually use opera refine to add some extra columns with information about all these files. You want to have columns a little bit if you're familiar with Betty, but this is very similar. You want to have columns with all the data that you want to upload to Wikimedia Commons so you want things like maybe a short description you want to have information about the creator, the license, the date when the file was created, etc. I will now go ahead and do that. And we have, I have proceeded with adding some data about my files here in my open refine project. I have created a column with the file names as I want them to appear on Wikimedia Commons. And for people not super familiar with Wikimedia Commons these need to be unique so you will see that. I have created unique file names for every file. My original files had very nondescriptive names like image 8025 and I improved that. So I have created a bit of a description in the inside the filing that's best practice. I have added short descriptions captions, which will be added as file captions in structured data. And in my native language touch, I have also added a column of the things that are depicted in the file because I want to add that as structured data. And I added the date when the files were created all in 2020. And I have also created a column with wiki text. For refine as I said focuses on structured data, adding structured data to files on commons also when uploading, but files also need to have wiki text and for that purpose. When you do an upload. It's good to have a column of wiki text. You can also add wiki text in another place I'm going to show that later. If you have diverse wiki text across different files which I do in this case, you see here one file that shows the windwall and another file that shows the artwork in Belgium. You see that wiki text is slightly different. So I have a column with that as well. You may notice for the wiki media commons geeks that is wiki text is super simple and I will talk about that later. Basically because we are adding structured data, we can keep the wiki text simple because it will be auto filled by the template on wiki media commons. So it will automatically show the structure data, which is awesome. Cool. Let me make my screen a little bit smaller again. The next steps that I need to do is actually before I can start uploading these files is I have to make open refine aware that it should work with wiki media commons. And that it should be editing wiki media commons and that it should be adding files there and that it adds should add these these things, which are not just text strings. So open refine discover these as wiki data items. So there is a wiki data item for the Rosenberg windwall. This really big windwall in concrete near Rotterdam. And there's also a wiki data item for that artwork. Basically this one. I opened it in my image browser. So I want to make sure that open refine knows about wiki data items for these. So I have a few steps for that. And the first thing I'm going to do is, I am actually going to tell open refine. Hey, open refine you are now going to edit wiki media commons. Open refine is able to edit wiki data wiki media commons and wiki basis so anyone who manages a wiki base can also edit their wiki base. And you basically have to tell open refine. Okay now in this case you're not editing wiki data but another website. You do and all of that is also explained in the Google document again. You select under the wiki data extension menu here and over refine you say, I am going to select the wiki base instance that I want to work against. And, oh, I already have wiki media commons here I will remove it. In this menu here you see a link that says discover wiki base instances. If you click that link, it will open a new tap in your browser. And then you will go to a GitHub repository that has various what we call wiki base manifests. These are various settings files for different type for different wiki bases. There is of course wiki data itself, which you will actually don't have not not have to enter into wiki data because it is there by default. And there is also the rise on one rise on has a wiki base. That's a cultural institution in New York, but there's also one for wiki media comments, I'm going to click that one, and then you see some code here, which is basically the settings file that open refine needs to know how wiki media comments works. I can either copy that code and paste it, or I can go to the raw and then raw version of this code, and then click the URL of that. And I can add that URL in here, or I can paste the JSON that I just saw. I think the URL is slightly better because then, if this JSON ever changes in this GitHub repository, then yeah, this URL will help to keep it up to date at wiki base. And now I have added wiki media comments, and I am going to select it just to make sure that it's blue. And now open refine is aware that it has to work with wiki media comments and not with wiki base. Okay. And now there's one intuitive, not very intuitive thing that you need to do. And that's a feature that we want to add we want to improve this we have ideas to improve this. You basically have to tell open refine that it needs to create new items needs to upload new files for this column. And now to do some things. I'm going to say reconcile, start reconciling, and I am going to reconcile this common this column against wiki media comments. Basically what I am doing here is, I am going reconciliation is actually looking up a list of values in your data set and looking it up against another database that can be wiki data wiki media comments. And in this case, I'm looking up the file names on wiki media comments, but they don't exist yet and that's totally fine. So, my reconciliation is running. And that will take a few seconds. The reconciliation is done. And if these files would actually have existed already on wiki media comments, the links would have been blue. I would have had blue links here hyper links and I would have had a little pop up showing me Oh, this is this file this is this file and I could click it and go to the file on wiki media comments. But obviously I am creating new files here. So, I am actually now going to tell open refine again here under the reconciliation menu, create a new item for each cell, and basically that will tell open refine that it will have to upload new files You see now that each little like cell in the data grid has a new label. This one. And the column has also has this bright screen underlines. Yeah, line, bright green line. And that means that it's open refine now knows Oh, I am working with wiki media comments and I'm going to create new files for you. And another thing I want to do is I will actually I would like to look up the wiki data items for these two things the Rosenberg went well, and the artwork by Daniel Buren. And for that I am going to do exactly the same thing I am going to reconcile but against wiki data. I'm going to say, I will do that a little bit slower here. Under each column in open refine, you have a menu with all the powerful things you can do with that column. Yeah, that menu is for most columns the same, you have reconcile at the bottom, which means look up in another database, start reconciling. In this column, you will already have the wiki data one in here and when you edit wiki media comments just now what I showed you, you will also have wiki media comments here. I am selecting wiki data. And then, yep, why not installation artwork. It will look up what I have in this column superficially and it will kind of try to guess what kind of type it is what kind of instance of it is. I have two artworks, public artworks, so this is probably quite good installation artwork. Sometimes when you have a column with really mixed things you can just say reconcile against no particular type, which I'm doing here, but I'm super happy with installation here and I'm gonna say starts reconciling that will also take a few seconds to do when you have really big data sets this takes a while so whenever you want to do this and you have a lot of data taken to account that you need time because this algorithm needs time to look up things on wiki data. Now we see that it has found this work. This is a work by Daniel Burin in Newport Newport. But it has not yet found the Rosenberg wind wall. I will just search on wiki data, because it's probably not described as installation artwork. And now I have matched this as well. So, my two values here have been matched I'm super happy so you see that the links are blue. I can actually click on those links, and it has linked those cells or refined has linked those cells to the wiki data item.  But I want to upload my own photos as well, because I created nice photos. So, basically my data set is now ready for preparing it for uploads. You see that some data is missing. Of course, I need to add information about who created these files, I am the photographer. There is not information yet about the license well there is some here in the wiki text but they also want to add it as structured data, because it's the same for all the files I will do that at the later step. And that later step is called schema building. So the next step is you are going to go to the next step here in open refine you have the type of your rose that you're looking at. And then you can go to the tab schema. And basically here is where you construct the like, I would say the template in which your edit will happen, the structure data edit will have it. I will start by clicking, you can also access this by the menu here so that's exactly the same you go to edit wiki based schema and you go there as well. You say at media. And then I get some empty information that I can fill with the data that I have here. And I am going to do some stuff and maybe speed up the recording a little bit. The next thing you need to do is actually tell it. Oh, you need to work with my file names here. So, these are the files that I want to create new this is the column in which I recall south just now as I showed you. So this is the column that open refine knows it needs to create on wiki media comments. So I am going to drag that one it is underlining green here as the main thing that needs to be edited. I open refine is asking me for the file path. Well, I have that here. So I can drag that column here. So it will take actually the values of what we have in the data set here. And it will input it there in my schema. And then the filing that I want to give it. I have the wiki texts. I can also add captions. I want to add the caption in English. And that's this one. I want to add a caption in touch in my native language. That is this one. And then I can also add some structure data statements. And there's some statements I'm going to add is what it depicts the pics and then it depicts the artwork that I just reconciled so it depicts this thing. You see that it also has the screen line below it. It shows that it has been reconciled against the database in this case against wiki data. And I am going to add some more information, like when the file was created file and some more stuff like who created it's a broader etc. All right, I am ready. So basically some basic statements. And of course this looks extremely abstract. And I actually want to preview what that will look like when I upload this file to wiki media commons it doesn't look fully like wiki media commons of course but it is a little bit of a preview. What each file, what kind of data it will have. So if you click here in the preview tab, you move from the schema tab to the preview tab. Then you can actually see each individual item or the first, the first ones of the set that you have here. And you see actually the specific data that it will add so you see that it adds depict statement source of file copyright license copyright status etc. And in the issue step. In this case it only tells me oh Sandra watch out you will upload new files. Well that's exactly what I want of course I need to be careful doing that. But if there would be things wrong here like for instance I could have made a mistake in formatting the dates etc. I would also get notifications here about that. So I think my preview looks rather good. And I am ready to actually do my uploads to wiki media commons. So to do that, I can go to the extension menu again here extension, the wiki data extension, and I select the menu item upload edits to wiki base. And then I only need to look in. I can, I should actually double check here that I am indeed working with wiki media commons. So we get a little local here and it also says wiki media commons if I would still have wiki data as wiki that it would show wiki data or it can show wiki base but in this case I added wiki media commons. And I am going to enter my credentials here. That's now, and I am looking in. And then I create an edit summary. So this is the edit summary that every file will get on wiki media commons. So, I just want to say a big artwork photo craft in 2020, not on work. And I am going to say upload edits and then it will do the upload for me. The upload is running. And so the upload is done. I am going to go to my contributions on wiki media commons. I actually had to do a bit of, I forgot to add a statement so I did an additional statement afterwards. I am going to show you two things. And here's where I uploaded the files. And you see that with the edit summary of the file, you see one link that says details. If you click on that link, you will go to a tool called edit groups. And that is a tool also created by Pintosh, our open refines lead developer, which allows you to undo batches. And so I have made mistakes in this batch in this set of files, then I can undo this. I have to say I'm not sure if it will be possible to also undo uploads and tire uploads, because I'm not sure that wiki media commons allows that to any user. If I have, for instance, edits, additional circuit data statements to these files and I made a mistake, I already did that. I make mistakes all the time. I am a very confused person. Then I can just undo an entire group and that's also reassuring if you make mistakes, you can actually undo them. And edit groups also access for wiki data so people working with wiki data doing batch uploads there may be familiar with it already. I'm just going to click on one file here and open it in a new tab to inspect my uploads. And I actually want to double check if it went well because it's an animated gift. I created an animation for this artwork. You can see it shows the file captions that I added to the file. And although I used very minimal wiki text, you do see that it has that it is loading so it is basically this wiki text. Let me show you a bit bigger. I updated it a little bit to also improve my name. It is this wiki text super simple. And it generates this because the wiki text template is actually is actually lower driven and it loads. Yeah, data from wiki data and wiki media comps. So it shows information about the sculpture and about me as a photographer. So if we look at the structure data tab, you see that all the structure data that I included here in open refi in the schema has also, yeah, this is an additional edit that I did afterwards. That it shows that the structure data I added in the schema is also added to wiki media commons. And by the way, I forgot to say one thing. And this is an important thing. It is mentioned actually quite clearly on in this document here. Uploading files to wiki media commons is only possible with open refine 3.7 or newer. So for open refine our current version if you go to open refines websites. Then you will see if you click the download button that our official version at this moment is 3.6.0. But we always are working on new code. So if you want to download, if you want to do an upload to wiki media commons you actually have to use 3.7 and you can find it on GitHub. You can also include it as a link in this document under download instructions. Let me see download and install refine. And we go to open refines GitHub repository. And you have a header that is called snapshot releases. That's basically the latest code of yesterday that was built automatically. And you can download that for your own platform with those users. I would encourage you to download the one with embedded Java runtime environment we just noticed that that tends to work better. That's it. Sorry for forgetting to say this. It's important use 3.7 for this. And I welcome questions. If all as well you should be hearing me live now. I hope that goes well. I am now juggling with two computers. So please bear with me. I am trying to juggle this. I see that people have asked a lot of questions in the etherpads and I am super happy that I did this pre recording because I could simultaneously let the recording run and already ask questions. So that is a really efficient use of time. I hope my answers in the etherpads have been okay and usable for people. I would say I can actually see the chat and I see the etherpad in front of me. So if people have more questions, I will answer those still and I can answer these live now. Do we have any questions that people want me to answer live? I can also repeat some of the major questions that happened in the etherpads while I don't see other questions popping up because the answer will actually be nice for the recording. One main question that people had was this over refined support all formats. I assume that's all the formats that you can do on Wikimedia Commons. The answer is yes. In general, hesitation, we hope. We tried over refined that with uploading with many, many different formats already. I uploaded videos. I uploaded animated GIFs. Someone did PDFs. That all went well. However, we are still noticing some trouble, but for instance, big defiles. And I hear that these are also in general for any upload to on Wikimedia Commons quite thickly. So we are still looking into that. But in theory, we are indeed aiming to support all the formats that Wikimedia Commons also supports. I think that's important for the recording because I did not mention that in the video. I see that there is a question. Are you still looking out for beta testers? Yes. I know this. I cannot discover all the mistakes that the software currently has. I cannot discover all the flaws. So actually, the Google Doc that I shared, you can use that on your own to your first uploads. And if you encounter any issues, either report them on GitHub. If you feel okay doing that, it's really, GitHub will not bite. We are super happy if people support issues on GitHub or just get in touch with me. And I will then help you one-on-one and also report issues. We already have some people doing that, but more is better because more I will see more things and also have more ideas for features that we need. So yes, please, please test. If you have materials to work with, I will be grateful. As you see, the current state is still a little bit experimental. We will add some features that will make it a little bit more user-friendly. But yes, that should be very nice that people do beta testing. Let me see. There was one thing I also did not mention in the video, but I think it's also really good for the recording. People are asking, maybe some people have trouble installing OpenWiFi. Normally, if you have a normal computer and you use a browser on that computer, you should be able to install it. But sometimes at work, people have firewalls or there are connectivity issues or something like that. So we do have cases where people cannot really run OpenWiFi very well because they are in a work environment where they cannot install any software. We also have OpenWiFi in the cloud for Wikimedians, and that is on POS. And I put that in the etherpad as well. Maybe it is already getting hidden among all the nodes. So I will also put that link in the chat here. POS is basically, and I have to use the right keyboard, I'm sorry. It's basically a cloud place where you can run all sorts of scripts, but we also have OpenWiFi running there. I do have to say it is not managed by us OpenWiFi itself. It's run by the very enthusiastic volunteers that do the POS installation. And we have been having a little bit of difficulty installing the last version of OpenWiFi. So 3.6 is not there yet, and that's a bit of a hassle. So please bear with us if that one is a little bit unstable. We're doing our best. We're doing this also mostly with little budgets and many of us as volunteers. So we do our best to support you there. Let me see if there are more questions either in the chat that have popped up new or that I can answer here. I see a question, offline data verification, can that be done? I'm not sure if I understand that question. I'm very sorry. That doesn't really give me... I actually don't know what you mean. I feel a bit blonde now. But if you have a bit more explanation about what that is or a link, then I will still try to answer that question because I am intrigued actually. Let me see. I will scroll down and see that there are other questions. I got a suggestion to look at photomechanic. I am curious what the tool is because I am not very familiar with that. A general question. Yeah, so indeed the pause that we just talked about that still runs an older version. I am sorry for that. So when will 3.7 be released? We are working really hard to have that released by the end of our funded Wikimedia project, which is the end of October 2022. My colleagues are working like beasts to get that done. Is it possible to use OpenRefine for batch editing of Wikidata records? Yes, and that has been the case for quite a few years already. So any current version of OpenRefine, you can use it to edit Wikidata. That is actually where it all started. Wikidata editing has been the first Wikimedia implementation of OpenRefine. And now we are adding the common one, but the Wikidata one is really the old one that many people already do and is really well tested. I can try to find a link to our info page on Wikidata, but if you Google Wikidata tools, OpenRefine, you will find the info page about that. I have a batch of TIFF files I want to upload. What do you recommend? Can I just give it a try or should I convert them? I would just give it a try. If you are okay with being a little bit of a test, how do you say that? A guinea pig, a tester? We would actually really appreciate if people want to try the TIFF files. I don't have TIFF files lying around randomly. So if you have them, please try and let us know how it goes. Maybe it goes well. So another question, and that's a great one. All the questions are great. Can OpenRefine get some metadata from the image or other files like the Exif metadata? Yes. Well, no. At this moment, not. We have been thinking about it since the start that that would be really, really handy to have. But it would require us to code something very specific of Exif retrieval inside OpenRefine. It's absolutely not impossible, but we cannot do it in the current grants. We are already working super, super hard the night to finish the basic features we want to have. And Exif is a wish that we know is there, and we cannot support it yet. Maybe if we get another follow up grant, we hope that that could be something we can do. I did include in the Google document though, with the instructions for Wikiday, for Wikimedia Commons batch uploading, the one that I talked about a few times in the recording. I have included a small like note with instructions on how to use an external Exif script, which is really easy to use, that you give your files to that script and your files will then have a spreadsheet with all the Exif, and that you can feed them to OpenRefine. I've done that a few times and that works really like a charm. Basically, what we would ideally like to do at some point is have the same mechanic inside OpenRefine. Of course, you just give OpenRefine files and then it will read the Exif that you are interested in. So we know that the need is there. It's just, yeah, that's for next iteration. Thank you for making notes of my answer. That's awesome. Is there any chance of getting David Turing to create some new tutorials? He has a fantastic voice. I have never heard his voice. So that would be great. I don't know. I've been working for OpenRefine for a year now and I have never been in touch with him. So I don't know the guy. I just know that he created the tool at some point. But I will keep that suggestion in mind because who knows, you know, it would be nice. Yeah, if you have other suggestions for people with good voices who should do tutorials, then keep us posted. Let's see. Do we have other questions? Are we done with questions? I'm also looking at the chat. Ah, what were the solutions for batch uploading before OpenRefine? There were and are still a lot of solutions. Many people use bots. If you are a programmer, you will be inclined to write a bot for your batch uploads. That's where all the batch uploads started. And then other tools came around a tool called Petipan, which has been broken for a while in the past year, but it's back up. Petipan has been repaired, so you can use it again, but it does not do structured data. And I expect that Petipan will also not support structured data in the future. Structured data is a quite complicated thing to add. And I can imagine that people will, I would really like to see that people move towards OpenRefine. So I really hope that people are open to start using OpenRefine. There are quite a lot of other batch uploading tools. If you Google Wikimedia Commons batch uploading, you will find a few instruction pages that lists various tools that are popular for that. Another one that has been quite popular, but that one is also sunsetted. It does not work at all anymore. It's the GlamWiki toolset. That was a really, really powerful one where you could input XML files where cultural institutions could do really complicated things with their databases and pushing their databases to Commons, but that one is gone. And there are other tools still around. But in my biased opinion, OpenRefine is a really good addition to that because it adds so much flexibility. It is very possible that you use Wikibots, yes, because that's the bot framework that a lot of bots programmers are using to write bots. So if you do some scripting, then that is your place to go. And I see that Alex has also made some information about other tools. Wikimedia uploader is indeed, I think, still used. I don't use it myself, but I know the bot tool. I see here that the counter has done. I'm not sure if that's really hard cut or if I am now not hearable anymore by anyone. But I think we are a bit at time for this session. So I will check out the tutorial by David. I am very curious to hear his voice. I really hope this was informative for people. And as I said in my recording before, I will be back. We will be back with more tutorials and training. And I really hope many of you show up there and we can start a small community of OpenRefine users for Wikimedia Commons. Thank you. Yeah, in my case, the screen says zero type remaining, but I can apparently just keep going on. Yeah. All right. Hello, everyone. And welcome to this session about the Wikimedia Language Diversity Hub. We will be talking me and Sadiq. Let me just share my screen. Here we are. All right. So this is to talk about Wikimedia Language Diversity Hub and the status of our research results. So my name is Ion Haralsobi. I work in Wikimedia Norge and have been a Wikipedia for about 15, 16 years. And for most of the time, I've been working with amongst other things with small language communities. And I've also been part of the Wikimedia Language Committee since it was started in 2006. And I'm also an administrator on the Wikimedia incubator and trying to help out with some technical stuff there. And with me, I have Sadiq who can introduce himself. Hi, everyone. I guess everyone can hear me. My name is Sadiq Shahadi. I am based in Tamali Ghana. I'm currently serving as the West African Language Coordinator at Art and Feminism. And also co-founder and the Executive Director for the Darbani Wikimedia User Group. The Darbani Wikimedia User Group is a Wikimedia affiliate language user group based in Tamali Ghana. And our work cuts across multiple indigenous languages like the Darbani language, Gumi, Mori and many other Moli Darbani languages. We are currently working to support about 16 Moli Darbani languages. Our main focus is Wikipedia and Wikidata. And sometimes we contribute projects related to Wikimedia Commons. I am also a steering committee member for the Wikimedia Language Diversity Hub. Currently working with a curationist as a social media manager. Thank you. Right. So a lot of you are probably wondering what the Wikimedia Language Diversity Hub actually is. And the idea is that it's an initiative to create a hub for everyone in the Wikimedia movement who is working on small and underrepresented languages. And if you're wondering what the hub is, that's kind of a bigger question. But it's one of the initiatives from the 2030 strategic process to create Wikimedia hubs. And this is an idea for a hub that is for, you know, small and underrepresented languages. And our goal is to make it easier to start and contribute to small language Wikimedia projects and to make the voices of the contributors to such projects heard. Gumi, I hear a lot of noise. Sorry. All right. So, yeah. The idea for a hub was, well, we started the hub idea late last year. But it's not an original idea because it builds on the amazing work that's been done already in the Wikimedia Language Diversity Group on Meta, which was started in 2012. And that's a lot of interesting people already. So we're not working in a vacuum here. But a lot of the, the idea for, you know, a more formal structure like a hub came from as a result of the Celtic Nut Conference, which were organized by Wikimedia UK. And during those conferences, we had a lot of talks with people who were working on smaller languages and realized that a lot of people were doing, you know, if not the same, then very similar work across many different languages, but not necessarily knowing what other people were doing. So we thought it was a good idea to try to, you know, get a better coordination for all this kind of work. And the Wikimedia, the hub currently is led by an interim steering committee with members from different parts of the world, some from Europe, some from Africa, some from North and South America, and some from Asia. So we have a pretty good geographic spread at least within the, within the steering committee. Yeah. And last, late last year, we applied for a grant to conduct a research project, which Sadeq will tell you a little bit more about. Can you hear me? Okay. So if you can hear me. So last year, we applied for the movement strategy implementation grant. And we're one of the selected communities to embark on the research project. Part of the projects includes working with indigenous languages communities selected from various parts of the world to understand how the hub project would look like and how we can better support these communities. We are at the early stage of the research, even though we have started like engaging some of the communities, and I will be sharing more about the communities that we have selected to work with. The selection was done by the steering committee and other partner groups to make sure the communities are truly diverse and we can get people from every part of the world. We want to have more representation for this particular set. We had a committee that reviewed the proposed committees that were shared, and we finalized that by making sure that we have selected the right committees to work with. So I will be sharing more about the list of committees that we have selected who will be taking part of the research. As I mentioned, we are at the early stage of the research and we have already engaged some committees in Asia and currently engaged in the grant between the committees. So John, if you can move me to the next slide where I can share more about the committees that are participating in this research. Next slide. John, if you can hear me. We have these selected committees we have based in the East, South Asia and Pacific region. We also have Mon Wikipedia based in East, South, East Asia and Pacific region. We have the Uyunaki Wikipedia which is still in the incubator in the Latin region, Latin America region and the Caribbean. We also have the Dibana Wikipedia which is in the Middle East and Africa. We have Ibo Wikipedia which is also in the Middle East and Africa. Then we have Greeny Wikipedia incubator also in the Middle East and Africa. Then Nigerian Pigeon Wikipedia still in the incubator also based in Middle East and Africa. And we have the Talish Wikipedia also based in Middle East and Africa. We have the Inaris Sami Wikipedia based in Northern and Western Europe. We have Angeka Wikipedia in South Asia. We have Kashmir Wikipedia in South Asia and then Atikami Wikipedia based in the United States and Canada region. Then the final one we have the Nahuatl Wikipedia based in Latin America. So these are the languages that we have carefully selected to participate in the research project. As you can see we have so many communities coming from Africa and Middle East and Africa. We also try to work with both existing and incubator languages so that we can understand the different challenges that the existing Wikipedia face and other incubator communities. And as I mentioned the idea generally is to understand how the hub will look like and how we can support these Wikimedia language specific communities. At the same time providing robust solution and also supporting them with the necessary skills and resources needed to improve or expand their scope of work. This is what I can say for now about the communities and how we intend to involve all the selected communities in the research project. John, do you want to add more? Yes, thank you. Let's just go to the next slide. Yeah, so we are looking for more people to get involved in this work because obviously this is a group endeavor and we know that there are a lot of affiliates and communities who are working with smaller languages and we would very much like to get them involved in the hub. And yeah, and that's not only for affiliates but also for individual contributors. So if you go to the link on the slide you can sign up to be informed and there are no strings attached like there's nothing you have to do but just to stay updated please sign up on that list. And also if you have technical skills we need to improve the Wikimedia incubator. So if anyone wants to help me do that then it would be much appreciated. Yeah, I think that's it. Thank you very much everyone. So if you are participating in this session you can follow us on Telegram. Everyone is welcome to join the community whether you are working with a language community or you are involved in language specific project. Just reach out to me or John so you can be involved in our project. So if you have any question you can drop it on the etherpad. So at the end of our presentation we'll have time to go through the questions and we'll probably interact and get to understand the topic better. This session will be divided into two parts. I would take the first part then Jeremiah would come up and take the second part before we attend to the questions. So where the presentation is on you can drop your questions and we'll attend to it all at once. So I'll be sharing my slides and thank you everyone for joining us. So I'll be sharing my slides right now. So Jeremiah can you please just confirm that my slide is visible? Yeah, it's visible. Okay, thank you so much. Like I did mention, my name is Omorodion Okwangai. My name is Omorodion Okwangai and we're looking at climate change. It has become a global consign as to how we treat our environment, how we treat the planet and how we treat the environment because issues surrounding climate change are becoming important issues today because it did not just affect us as individuals, it affects the entire ecosystem from the human perspective, even up to marine lives and other lives. So that's why it's attracting so much attention. And today we are calling on so much action to be taken so as to help combat climate change. But as we go further, we'll look at what is our responsibility because it is not just for governments alone. As individuals, we also have collective responsibilities to play in order for us to effectively combat climate change and achieve a sustainable environment. But first of all, what do we understand by climate change? Now, there have been different explanations as to what constitutes climate change. Why some have defined it as extreme weather conditions? Different school of thought have had different definitions. But the one that struck me was the one defined by Amnesty International in 2022. They define climate change as rising temperature and also extreme weather events leading to rising sea levels and shifting white populations. But also, the United Nations gave a simplified definition to climate change. They defined it as a long-term shift in temperature, which has resulted in change in weather patterns. So this increase in the Earth's temperature source has led to extreme weather pressures. For example, it's rainfall in some areas such that it has affected the safety of different regions. Then again, there is also the manufacturing of goods, products, transportation, all these on its own generally because of probably what we tend to use. They tend to help, they tend to, on the long run, affect our climate. That is why there is an urgent call for the use of renewable energies, for example, wind or solar, so that we can actually reduce the burning of fossil fuels so as to help save our planet. Now, I'll leave you with a perfect description of what we talk about when we talk about the causes and its effects. Sorry, I'll just go back to that slide now. I want us to take a look at this slide. It gives us a pictorial illustration of the causes of climate change, how it occurs, and its effects on the long run. Now, we have seen, for example, that too many causes is deforestation or cutting down trees and also fortified combustion, which is the use of coal, gas, oil for our different activities, whether it is production or it is transportation or whatever it is. Now, all these leads to what we call greenhouse gases. Greenhouse gases. And the major greenhouse gases that leads to climate change are carbon dioxide, which is our CO2, which is our CH4, nitrous oxide, and water vapor. It is when these gases trap the sun rays in the atmosphere, it allows the Earth to eat up and thereby lead into global warming, which has a... You know, because it has a system. It is a system. A change in one state probably affects another aspect. So, for example, when there is a change in weather conditions, it can lead to droughts. And when it is cold and reduced, it can lead to famine. And you see the system, it goes round. That is why it affects the system. But it is very imperative that everyone collectively join hands together to address climate change. And we are coming up as Wikimediands. What can we do as Wikimediands on our own path to address climate change? So, apart from causing famine, for example, there are also other dangerous effects of climate change on the long run. What we have witnessed in recent time has been a consistent increase in the Earth's temperature. Now, if we continue to do what we have been doing, say, in the last four to five decades, if we continue to do it till the end of this history, it is going to be much more difficult for people to live in some places in the Earth, say, in the next century. So, what this means is that places like Saudi Arabia, for example, the Sahara desert would be too hot for some persons to live in. So, just to summarize what I have been trying to say, climate change, part of its effect is Earth's temperature, which also, when there is Earth's temperature, can lead to increased white fire. And when there is equal white fire, we know that there is going to be loss of plants and animals. And we know that also, we are going to experience loss of biodiversity, which we are already saying. Then also, there are other effects. I know, perhaps, many of us may have been familiar with, oh, that there may be lots of species, not enough food, when there is, as a result of climate change. But there is one striking effect, which was as a result of the finding by International Crisis Group. It explains that one of the effects of climate change could be increased conflict in some region. And it gave an illustration, for example, in Nigeria, which is the western part of Africa, that climate change, which has led to drought in some areas, has led the headers to move into the southern part of Nigeria. And it intensifies the already existing conflict in many areas in the southern part of Nigeria because these headers are in search of water, in search of green pasture for their animals. And as a result, they have consistent clash with farmers. So in a way, climate change beyond just leading to increased drought or beyond leading to loss of species, it adds a way of intensifying conflict in regions. Now, the effect is just so numerous that if we decide to say let's start analyzing one after the other, we find that it's something that we all must actively, we must actively put us together to fight because its effect on the long run is going to be very devastating. In the United Nations, the World Health Organization explained that climate change is the most, is the single most, I'm not sure, single most devastating health condition that it has ever seen. Just to paraphrase what the World Health Organization said regarding to climate change because a change in temperature is going to lead to increasing changes in some, is going to lead to increased amount of some temperature related diseases. So these are some of the effects that we have seen in climate change and there are some statistics, some key facts to back up some of these things. For example, it was recorded that the concentration of carbon dioxide in our atmosphere at start July 2021 was around 400 and the same past per million. Now, this is staggering compared to the last three decades we've had. The conservation.org identified that deforestation alone contributes 11% that is significant, 11% of the total greenhouse gas. Now, you can imagine when we decide to say, okay, let's address deforestation, for example. Let's try to reduce the cutting dam of forests or trees and how much we'll be able to save carbon dioxide. So, part of the fact we have seen is that we have already earlier many is for the total greenhouse gas emissions. You got my sign, I'll just quickly run through. So tropical forests. And tropical forests are very likely to reduce the cutting dam of forests or trees and how much we'll be able to save carbon dioxide from going into the atmosphere. So part of the fact we have seen is that we have already earlier many tropical forests can provide at least a third of the total climate change mitigation actions. A third of the total climate change mitigation action. Yes, this solution only received about 30% of the total climate funding. So it therefore raises question as to what exactly are we doing to address climate change. Apart from, yes, having discussion here and there, and we actually make it action in this regard, like planting of trees so as to address climate change because statistics have shown that planting of trees and forestation actually contributes significantly to the fight against climate change. And as of July 2021, the National Oceanic and Atmospheric Administration of the United States reported that July 21 is the hottest month in human history. Now that is a staggering fact. Just last year, July 2021 is the hottest month in the whole of human history. Now, since 1980 to this, we have had consistent increase in the Earth's temperature, consistent increase. It therefore shows that there are things we are not doing correctly that we must address. Now, July this year was the third hottest month in the United States as reported by the National Oceanic and Atmospheric Administration. Costa Magus also saw up 10 times carbon per hectare as tropical forest. Despite being just 0.7% of world forest. Now there is a lot of staggering facts. If I should start bringing them up, not to look all the facts, but the fact is that attention, we all need to start paying attention to climate change. And the action starts from all as individuals. We are uprooted to play. Having an understanding of the cost gives us an insight as to what our responsibilities are as individuals. Now some countries have started taking themselves, are taking significant steps. For example, has the creeping. You look at countries from, for example, in Africa and Asia countries, which in the end may actually have them. Asia and Africa, for example, those many of many actions are still needed in order to successfully address climate change. But it is wanted to note that about 190 countries have ratified the Paris Agreement, which seeks to address the release of greenhouse gas. So apart from climate change, we've all been talking about climate change, doesn't mean that there are no other environmental issues in Africa, for example. Of course there are, but somehow they are interrelated to climate change. For example, we have Africa in many countries in Africa, even in Nigeria, we've experienced water pollution, air pollution, as well as land degradation, which in a way are also connected to climate change. And we've also had differentiation, lots of biodiversity and so on, as different challenges which constitute, which affect the environment. But the truth is that we all have responsibility to address this change. If we must, if we must achieve a sustainable environment and on the, on the long run achieve the sustainable development goals. But what exactly are our responsibilities? How do we save the planet? Not if we were that, if we continue in this trend, the next century is going to be very difficult for the next generation. How do we then save our planet? And how does Wikimedia come into play in this regard? So I'm going to hand over to my colleague, Jemaya, who is going to take us through the solutions and how Wikimedia projects can help in combating climate change. So Jemaya, over to you. All right, thank you, Mr. Amorador. That wonderful introduction. Okay, I'm going to share my screen now. So I'm going to be starting from, how do we save our planet? Mr. Amorador has made mention of a lot of issues associated with climate change. If we are not careful in the coming years, in the coming months, in the coming weeks, it may be done with so many sicknesses, not because they came out from nowhere, but because our activities, our behaviors, can be linked to be the cause of factors in respect to this climate change. So what do we do to remedy this situation? What do we do to save our planet? So what part of what we are going to be doing? I'm going to divide our role into three hours. Reduce, reuse our cycle. What do I mean by reducing? It's time for us to reduce the contamination. A lot of us are careless with the way we handle things. A lot of us, when it has to do with plastic, we dispose there. Wherever we are, we just dispose them roughly. Some of those disposers lead to the blockage of the oceans, of the seas. Some persons in some countries in Africa also, you find out that they are illegal refineries. And all these illegal refineries always lead to a mission of bad gases on the air. And on the long run, these gases come back to affect the human. So it is time for us to reduce all this contamination. When we are able to reduce all of these, we cannot create room for reusing. Because if you don't reduce what you are doing, you cannot think about reusing it. So if we are talking about the aspect of reusing, it's time for us to start thinking outside the box. We have to pay attention. If we are talking about okay, we don't want to contaminate the sea again with our plastic containers, with our bottles, with our cans. What do we do with those cans and bottles? It's time for us to now start thinking about how do we refine? How do we convert these cans and bottles so that we can be able to reuse them effectively? How do we convert these air, these gases that are emitting, these activities that we are doing that it seems as if, wow, we are causing a big problem to the planet. How do we think about reusing it? And the perfect way to reuse them is to recycle them. It's time for us to pay attention to recycling. As a matter of fact, a lot of countries are already doing that. Some of them are already recycling their nylons. They are recycling their bottles. They are recycling their cans. A lot of them, the years of flushing water down the septic tank into the reservoir is gone. Those waters, they channel them to farms to other areas where they can now recycle. Instead of wasting that water or on the long run, it gets to the ocean. Now, they recycle it and use it for something else. Now, these are the roles we have to play as individuals if we want to save the planet, because we have to save the planet. One of the great philosophers talked about, if you don't save the planet, there are no two planets.  The moment the air is contaminated, the moment the land is contaminated, the moment the sea is contaminated, it will also affect you on the long run. Now, also as Wikimedians, what is their role we have to play? Does Wikimedia projects such as Wikipedia, Wikidata, Wikicommerce, do they play any role? Yes, they play some roles in this aspect of climate change. Now, one of the roles I can say this is the most or the major role that these aspects of Wikimedia projects play is they create public awareness of these climate change issues through Wikipedia. By organizing trainings, by organizing a data tour, you create an awareness and through that awareness, you educate people. If you do a research on the project by the youth climate council in Ghana, you find that that project cuts across various aspects of Wikimedia foundation. And the idea behind that project was to create awareness on areas in Ghana that are already passing through this climate change issue. And also to open the eyes of the citizens to the fact that we can do better, we can change these. So in that aspect, you find that Wikimedia project has already created that awareness, that public awareness by campaigns, by taking it to schools, taking it to mosques, taking it to playgrounds, creating that awareness. Because a lot of persons don't know that the behaviors, the lifestyle they are living in is in another way affecting the climate, which on the long run is going to disturb us. Another role which this project can play is also documenting important climate-related data using Wikidata, using Wikicode. Through Wikidata, Wikimedians can come together and document data that has to do with climate change. Maybe in your location, something is already going wrong. And as a Wikimedia, you can see that, wow, if we don't rise up to the tax in the next two or three or four months, there will be issues. We'd like to give an example like something that took place in one of the areas in Nigeria. We find that after a while, a lot of persons began to fall sick and not just fall in sick, some of them began to die. And when the research was done, it found that there was some part of the mineral resources on the floor. Through illegal refinery, those resources contaminated the water they were consuming in that village. And before the authorities could take note of it, a lot of people had lost their life. But through Wikidata, through Wikicode, Wikimedians can come together and document these issues as they come up to create an awareness. And not just creating an awareness, but in return, send these documents, these data to the relevant authorities so that they can act early enough. And also finally, as part of this role, which we are supposed to play as Wikimedians, we are supposed to volunteer and not just volunteering, but volunteering to join Wikirrelated groups and campaigns that are focused on climate change. There are so many projects on Wikimedia, there are so many projects on Wikipedia, there are so many projects on Wikidata that are focused on climate change. And as Wikimedians, we must be ready to volunteer to contribute our quota, to contribute our quota in the society where you find yourself, in the locality where you find yourself. Where I am situated in Nigeria, there is an issue that has to do with climate change in my locality. And the only way I can come in now to change the narrative is to join groups, create groups, create campaigns that will open the eyes of the individuals to the fact that there are a lot of things that need to be done to change the narrative. And also, just as we are saying what we need to do also, there are also some other climate change related Wikimedia projects that have been done before. Some are also on the about to be done and some will still be done because I'm sure that after this training, after this conference, a lot of persons will be interested and we say, okay, it's time for us to change the narrative. We cannot continue to live our lives as if we, the climate, we are not causing a harm to the climate. The moment your eyes is open to the fact that you are doing something wrong. I think as a Wikimedia, as somebody that have the thoughts of the society, as somebody that want to live where, as somebody that want to live long, you do a lot of things to change the narrative. Now, some of the climate change related Wikimedia projects that have been done, some that's the ongoing we said there was the Wikipedia for Peace and Climate Justice 2021. This was done by the Service Civil International in Switzerland and this was in cooperation with the Wikimedia Switzerland. As a Wikimedia, you can search out there and know what they did, look at the areas they covered, look at how they did their project, because don't forget that in the Foundation, we talk about what are your outcomes, what do you expect to achieve. And all of these, when you put them side by side, it can also help you to conduct the same related projects in your locality. And also there was the African Climate Change Editor Turn, which had in South Africa in 2019. Some volunteers and some Wikimedias came together to create awareness by training individuals on climate change areas of Wikipedia, improving the content. And also, recently there was the Wikipedia, there was the advert for the Wikipedian in Resident Fellowship, which was the idea behind this is to help to fight climate denies in Africa in 2022. And many others, all of these projects are geared towards changing the narrative. And we have to change the narrative, just like Mr. Muradio has said, there are so many issues that consciously and unconsciously we are already affecting our climate. And if we don't rise up to the tax, if we don't rise up to the tax and doing that as soon as possible, we find that a lot of us will be stuck in the box wherever we are because moving forward, some persons may begin to fall sick with so many sicknesses, so many issues. You go for treatment and you can already fight them, not knowing that I was part of the cause for this issue. That's why as Wikimedias and as Wikipedians, we have to ensure that we go about changing the narrative. We are encouraging projects, joining project volunteering to change the narrative. And also, I want to share an experience we had as we are talking about the Wikiped for the climate change and environmental issues. Also, we will share an experience on one of our projects which we had in Nigeria recently and we targeted the Green Wikiped for climate and environmental sustainability in Nigeria with the case study of a new state. The project was a success and through the project, we found out that more than 40 participants with an average of 80% of the participants were all new volunteers from the adverts, from the campaign, from the awareness that was created before the project. We found out that a lot of persons are interested. They want to contribute their quota to change the narrative. And through that project, we found out that at the end of the project, we realized that overnight articles were edited and improved. Even though the awareness we were not able to cover the awareness the way we would have loved to, but you find that a lot of persons were encouraged, they were interested. Oh, this is what we can do. Oh, these areas, they need improvement and money more. And also through that campaign, we found that over 18.3,000 words were added and we also had 239 references added. And from that way you find out that we have been able to successfully document climate change issues in those states and in particular in Nigeria through that campaign. I'm moving forward from that because we understood and at the end of the campaign will notice that wow there's so much that needs to be done we have a lot that needs to be done. We decided okay that we are going to be moving that campaign now from those states to river states and we turned the campaign to wiki for climate and environmental literacy in the river state because we understand that you can only change what you know, you cannot change what you don't know. But before the individual, before the volunteer, before the student, before the community, before the youth, before the country, before the state can change the narrative, they must be aware of it. That is why we are moving about we want to create that literacy, open their eyes to the fact that so many things need to be done. There are so many areas that needs to be changed and we are also doing a pilot study in two schools and the schools in view in respect to this project of river state university, and we are looking forward that at the end of this project we are also going to extend this because we have a very particular issue in river state which prompted this climate change and environmental literacy because recently river state in Nigeria is one of the oil producing states and because of the attitude of the government, attitude of the individual, attitude of the citizen, you find that we have so many oil stillage, we have illegal refineries here and there at so many areas which are not supposed to be. So because of that you find that there is an issue that has to do with climate change, our air is already contaminated. If not then now that we are the rainy season now, if it isn't the dry season, you find out that when you look at this sky, you can't even see the blue sky anymore. You begin to see dark, dark sky, which is as a result of the black soup that is coming from all these illegal refineries because the authorized refineries they know how to dispose all of those air but these are the individuals that are just going about to get their money. They just want to do whatever they want to do and on the on the long run they don't know that they are contaminating the climate, they are contaminating the air in the state, moving forward in some years to come, in some weeks to come. You may find that there will be so many people in river state that will be done with cancer and cancer is not going to come through magic, it's going to come because of the air they breathe and the air they are breathing is not good. The air they are breathing is already contaminated as a result of this illegal refineries. That is why we as Wikimedia and I and my colleague Mr. Almoradon and also the Ponteva Wikimedia Hub decided to come together and say okay now it's time to take this campaign out. We'll be taking it to schools, taking it to market, taking it to the youth, taking it to the government also to open their eyes to the fact that we need to change the narrative. Because if we don't change the narrative moving forward, a lot of us will be sold down with various sickness. This is an experience for Nigeria and also an experience from river state which I'm trying to share in particular. And also as Wikimedias, just like as I'm sharing my experience from Nigeria, you also have the experience for wherever country you are listening to me from, for wherever state you are listening to me from. And it is time for us as Wikimedias to arise to the tax, to change the narrative, to ensure that we adjust, we complement, we turn things around in respect to climate because we do not have to climate. We only have one word, aside the earth we are, it's another planet earth together. Unfortunately, a good number of us are only living on the earth, we cannot live elsewhere. And also to end this my session, I would like to take a code from Chey Jean, we said, the strongest government on earth cannot clean up pollution by themselves. They must rely on each ordinary person like you and me on our choices, they must rely on our choices and on our way. So it is time for us to rise up and change narrative. Thank you very much. I'll hand over now to Mr. Moradion. Okay, I think right now we would love to take questions if we have questions from our listeners. You can drop them. Thank you so much, Jamia. I think I'll bring you the chat to why you were talking and I wanted to make sure that they and it's been very engaging in the chat. So thank you so much, Jamia, for highlighting some of the solutions to climate change and also how it's at the intersection between climate change fight and the Wikimedia project. And it's been the discussion also in the chat has been very interesting. There's also the Wikimedia for the development user group owned by Wikimedia within the foundation within the community, so that those who are interested in climate change fight and development can actually be a member of the user group. I would also be sharing some interesting information here. So, but I don't know if aside that I don't know if there are questions, other questions that you want to ask. I know some comments, some questions that have been answered from YouTube. So just quickly go for it. Sorry, I'll just clear it. Thank you, Brice. Brice noted that it is important to feel climate change information gaps in Wikipedia to create locally relevant content. And this, of course, I agree because closing the Wikipedia content gap is actually a crucial step to fighting the climate change. So we have to first of all address the knowledge gap and the information gap, because it is only when, as noted by Jamia, it's only when they know what the problem is that they can actually know how to combat it. And given that the fight is a collective fight. So there are a lot of comments here. So I was asking about the Wikipedia and residence link, which has already been shared. The residence that has been organized by Code for Africa. And also, and it has also been noted on the group that the Wikimedia UK also, they also set link for Wikimedia irresistible with a focus on the solutions to climate change. So there are so many information on the chat. But I don't know if you have more questions probably before our time runs up, we'll be happy to take the questions. So there is also an information on the group. There's also an information on the group that we'll be having. There will be training for local organizers who are interested in carrying out campaigns on climate and environmental change. They'll be training for local organizers. A message that was drawn by Alex in the group for those interested in organizing so you can reach the community via email can write to campaigns at Wikimedia.org and you'll be able to get the necessary support that you need. So I'm just trying to go through the chat to see if there are other questions. Just feel what we are doing is cool. I don't care. I can drop my trash. I can do this and do that. Even because of that lack of desiccate attitude. That's another weakness we have in respect to climate change information. But I think as Wikimedians, it is not for us to change the narrative. We should encourage those documentations by ensuring that our outreaches, our trainings are properly documented, are properly covered. If possible, you can invite government to all of those trainings because there are so many things they can learn from it. You can invite present individuals too because the moment you invite them, they begin to see that, yes, there is a problem and that problem needs to be tackled. I'm very sure that the information on climate change, both on Wikipedia and also on the internet on the phone will be increased drastically. There are so many climate change issues in Nigeria, some of the states, some of them they are already having erosion issues. Some of them golly issues, some of them flood issues, some of them the desert is crazily encroaching into their dwellings. So if all of these are not documented, how we didn't know how to solve it? Just like during my presentation, I shared the case of one of the locations where people began to foresee, some of them even lost their lives. And they didn't know what is the problem. It was after there was a test, some persons took it upon themselves and said, this is not normal. What is the lifestyle that is going on here? Maybe something is wrong here. And they began to test their water, test their food, test even the air. You find out that when they were done with those testing, that was when they realized that the water they were drinking had been contaminated by illegal mining. And because of that contamination, you know, anybody that consumes the water is as good as your system is trying to be a mess. So I think in a way to increase that climate information, we have to ensure that there are documentations, proper documentation and encourage our locality, encourage individuals, encourage STDs, SDGs, asides Wikimedia. You find out that there are also various project, SDGs project that has to do with climate change, encourage the coordinators, encourage the volunteers to ensure that they document whatever they find out. They document whatever they see, they document whatever they go to, just like the project in Canada was done. When you look at that project, you find out that, aside the editor turn aspect, there was also a plodding of pictures of areas that needed attention of various locations that were already being eaten up by climate change issue. And you find out that if the government, if people in government, if the authorities are privileged to layhound, layhound on those pictures, is a reasonable government, a government that wants its citizens to be alive. We spring into action immediately to try to change the narrative. So I think in that way, we can help to calm or fill up that aspect of the weakness that has to do with very, very poor information on climate change. Yeah, somebody says so regional documentation, Femke, yeah, exactly, regional documentation is very important. And also, from Alex, Alex said, you have to also ensure you reach out in the global south on topics that they will search for, for example, the cities, local government, local conservation gaps around water bodies. All right. So at this point, we are going to be rounding up now. I appreciate everyone for their time for being in this session for sparing time to listen to me. It's the German level and my colleague, Mr. Moradium, a con guy, we're glad to have we, we are glad all of you were on the call and we appreciate the questions and the contributions. Thank you so much. And we hope to see you again next time, hopefully with your elaborate and more interesting climate related topic. Thank you very much. Hello. Hello, everybody at Wikimania. Welcome to this session about the colonizing structure data. I am Mariana, I am with Zim, Kelly and Eta, and let me share my screen, full screen. So welcome to this conversation. This is an invitation from Whose Knowledge, Wikimoviment to Brazil and Wikimedia Deutschland for joining a conversation that started last year. I am Mariana Fosati, the Whose Knowledge, the colonizing Wikimedia program coordinator. I am with Erika Aselini, community manager at Wikimoviment to Brazil. And she's the project management of Knowledge Justice at Wikimedia Deutschland and Kelly Foster, my colleague at Whose Knowledge, the program coordinator for Whose Digital Archives. So this conversation just started, it started on October 2021 when over 40 participants from around the world started this conversation about the colonizing the internet structure data as part of a broader conversation about the colonizing the internet. These 40 participants were mostly female identifiers in or from the global south. They were mostly indigenous black people of colors in origin. And these 40 participants had together at Wikidata, at the pre-conference of the Wikidata.com that last year was held in Brazil by Wikimoviment to Brazil. And this pre-conference were organized between Whose Knowledge, Wikimedia Deutschland and Wikimoviment to Brazil. But for starting or restarting this conversation with you at Wikimedia, it's important to talk a bit about what does distributed data mean, especially for newcomers, because this Wikimedia is especially focused on welcome newcomers. So let me just say in much technical details that this is of information that can be easily read, understood and processed, not only by humans but by machines, especially by machines. Humans give dictionaries, the vocabularies, the ontologies to machines for understand us, understand the meaning of the objects, events, places, people, relationships that are part of a structured data system. And these systems are used in countless apps, tools, platforms on the internet that are built upon such as structured data systems from Google to Wikidata. For instance, let's think on the info boxes that you can see when you do a search on Google. For instance, the Google Knowledge graph or the Google Knowledge panel is made using data from different sources, structured in a certain way. And it's ready for answer your questions when you search online. And in Wikidata and Wikipedia are important parts of these kind of knowledge panels that you can see when you search on Google. But also there are other ways of using structured data. For instance, just yesterday in Wikimania we shared about Wikikitua, a database in Wikibase that can be used for instance for creating a chatbot in Kitua, in Kitua language for Kituan speakers. So there are a lot of different ways in which structured data can be used. And a way in which you can see structured data on Wikimedia projects is structured data on commons. This is something that I don't know if anybody knows about this project, maybe newcomers don't. But this is about the media files, the millions of media files we have stored in Wikimedia commons can be connected with concepts where their representations as data on Wikidata in a multilingual way. This is possible because every item, every entity, every object that you can find on Wikidata, which is a huge database, is identified by a call. This new follow up by a number that identify this unique entity, this unique object like a book or a light bulb or a computer or even a feminist strike, any event that you can find on Wikidata. But also in a multilingual way because every entity on Wikidata is available in many different languages. This is a collaborative database, commons is a collaborative media project, and both together make it easy for people for instance to search images in different languages and to let the search and shine on Wikimedia commons find images in a more contextualized way because the images are related with data in different languages. This is a way in which you can experiment directly structured data. And also you can contribute adding descriptions, linking the images with the data using Wikimedia commons. But beyond the technical, this session is about the political policy of epistemology in this technical developments. So why does structured data need knowledge justice? That's our question today. For different reasons, at least these four important reasons. Structured data is at the core of how the internet works nowadays. Currently, as I said before, you can find structured data in searching online, when you do questions to a voice assistant or when you look for a translation. You can find structured data everywhere, especially because artificial intelligence is deeply based in these datasets that are structured in specific ways. But these systems are far for neutrality because, and this is something that we bring all the time to the conversation in whose knowledge is that the knowledge that you can find online in which structured data systems are based that feed these systems are not mainly created for and by women, people of colors, LGBTQIA plus folks, indigenous communities and peoples in and from the global south. At the contrary, we are the ones that are more impacted by how structured data is used or even abused. So there is an urgent need for centering those who are often marginalized in the build, in the develop, in the process, in the uses and abuses of structured data online. For having this deeply political conversation, we at the pre-conference, at the wiki data pre-conference, we set the conversation based on guiding principles that are love, respect and solidarity because we wanted participants to be aware of their positionalities and privileges and to be able to be their full multiple self during the whole session. So that's why we grounded the session in these principles of love, respect and solidarity and also we had a commitment for the privacy and safety and well-being of the participants and also with language justice this session had a simultaneous interpretation between Spanish, Portuguese and English because the pre-conference was very focused in Latin America because the wiki conf was held in Latin America last year but also because at least if we can just bring a bit of language justice, this is so basic because language is a proxy of knowledge. Especially online, so that's why we were paying attention especially to that. So with those principles in mind and in practice, what did we do and how did we do it in that session? We organized this session in three parts, a panel called Perspectives and Provocations with the words of a special guest that shared their provocations, their deep provocations with us. Then a small group session with all the participants, split in smaller groups, called Imaginations and Implementations and finally a plenary called Listening and Learning in which listeners from each group reported back to the plenary. That was the organization of the whole session. The provocations of the panelists were about some specific questions. What does structured data mean and why it is important that we talk about it? What does it mean to have multiple knowledge frames, multiple epistemic frames or epistemologies at the heart of structured data? How can we rematch structured data especially from a feminist and anti-colonial lens? What is one thing you would like to see done differently in structured data today that will help us come to that space of emancipation and liberation? I want to invite you to keep these provocations in mind and share about this in the chat, especially by the end of the session today and especially the last question. But after this provocation and the small groups work, a key insight emerges from the conversation and let me share a bit about this. One of the topics was access and control of data. Who controls the data, who governs and who is excluded of data governance online? We identified here the need of granted fully access to knowledge and tools, especially to the majority of the world who is marginalized from data governance, to being able to participate in governance, to create, to develop structured data system, to use it, reuse it, process data. But also, and this is very important, we identified here a conflict between the actors that use structured data in commercial ways and for profits versus some human rights issues that can be in conflicts with such a profitable use of structured data online. Another topic was agency and engagement and here people talking about the importance that there are no excuses for people to engage with structured data, bringing the diversity of context and epistemologies that exist. And if we create knowledge resources and a full ecosystem based in this diversity, there is no excuse to not engage. But also it's important here to acknowledge that some specific knowledge, especially in indigenous communities, maybe shouldn't be online if the community don't give the consensus for that. And there is a right to refuse thatification especially for indigenous communities. Another topic was distributed data in a certain way, smarter solution in comparison in opposition to big data, maybe smaller and connected data sets governed by marginalized communities at a much better solution than big centralized database. And this is related with another topic, planet centered redesign of structured data keeping in mind the environmental impacts of data infrastructure and questioning the purpose of every new develop, every new data set, every new engine, every new artificial intelligence application, keeping in mind doing an assessment of these environmental impacts, especially the impacts of big data. And finally, the importance of the plurality of data and to create models based on different knowledges and the glorious complexities of our communities. The importance to go beyond text because not all knowledges can be encoded by text, images, sounds, signs, other ways. And also the importance of the local specificities and the critical need of listening because the colonizing the structured data, the colonizing the internet is a process, colonization is a process which needs time and efforts, intentional time and intentional efforts, so listening is critical here. So before I talk about what is next, I want to invite my colleagues to share some thoughts after these presentations. I will stop sharing and I want to invite Erika Sin and Kelly, maybe Erika, can you go first? Yes, sure. Thank you very much for the invitation for this conversation. For me it's a very special moment because it's been almost a year now since we did this event last year. And well, I think I can start from the beginning, right? So we were organizing WikidataCon in partnership with MediaDeutschland and we thought that this shouldn't be a conference just for people who are already in the Wikidata Universe and heavily focused in their contributions in there, so we wanted to take the opportunity to bring more people to the conversation. And we also didn't want this to be a technical conference as well. We wanted to focus on the social side of Wikidata because Wikidata is constantly growing, is scaling up at some site. And still there are a lot of people who are not in there, so this implies in how structured data on Wikidata is being organized at this moment and who are not there, so which knowledge are not there. So this conversation we had was very important, not only because of the content itself, but I think of the methodology that we use for the event. So the way that we selected people to attend the session and the way that they were invited to provide their thoughts as well is very important for not only the engagement but for the way that they feel that their ideas and perceptions are received and welcomed and valued at the same time. Because this is not something very intuitive in other spaces. So the way that we organize this sort of conversation may be as important as the outcomes of the conversations as well because it helps us to build stronger connections in people in communities who have been marginalized from such processes. So this is my perspective on everything that we did. I feel that more than the outcomes because we'll see in the long run, not on the short run of course, but how we make this done is very important as well and I'm really proud to be part of this and thank you so much for being here. I'm really curious to see what my colleagues here think about what happens in the near future as well. And thank you so much. Thank you, Erika. Thank you so much. And I will pass the word to Asin. I hope you can hear me. Yes. Oh, sorry, I can't hear you now. I don't know why. Okay, again. No, no, I can't hear. It's audio, the bane of humankind for forever. But yeah, I joined Wikimedia Germany actually like two months ago. So I wasn't present for your conference last year, but I still witnessed it as a person outside of Wikimedia. So I'm super happy to be here and I'm kind of honored to like, yeah, working on knowledge equity with you and other communities. And myself, I have a background also like in tech and intersectional educational approaches to it. And I would totally agree that we also have like to get to the point that more people just like learn and know that tech and structured data is not neutral and not objective, but it's like created and formed by people and their beliefs and perspectives. And as of now, like very specific kind and group of people. So we definitely have to change that and also let people know about it because most people just, yeah, don't know they think like it's a physical science but tech and data is not like it's just so influenced by people. And so I think this would be a first step, definitely. And also a lot of people still have to learn. And yeah, like we are building our team up in Wikimedia Germany that's like where I joined two months ago and other colleagues as well. Because Wikimedia Germany, yeah, in the Wikimedia universe has a lot of researchers to share. And that's what we're here for, like we want to get engaged with marginalized communities, get their perspectives and of course share our resources and support them in their work. So thank you very much. Solo hablo un poco español, pero puedo decir muchas gracias a todas para nuestro trabajo. I hope this was right. So thank you so much for your work. Muchas gracias y muy bella escuchar tu palabra en español también. Thank you. And Kelly, please go ahead and share some thoughts with us. Thank you very much Mariana and hello to the other panelists. My name is Kelly Foster and I attended both the workshops that were done to produce the decolonizing the internet structured data reports. And I was part of the programming team for Wikidata con last year as well. So a couple of reflections really all to emphasize some of the points that Mariana brought up in the presentation. And one of the key themes that I remember from the workshop was around the right to refuse datafication and the right to opacity, as it's called by a Martin Eakin philosopher Edward Glisson, the right not to be understood. And definitely in the sessions that I was in that was a strong theme. How can we the big we the global we humanity we how can we ensure that we respect people's rights not to be understood and right to refuse datafication as the report put it. And the other thing reflecting on the conference last October in discussing decolonizing the internet or decolonizing structured data. One of the things that's less able to be communicated by a report or even by the by the recordings of some of the sessions was the very palpable pain that came along with the of the discussions that were being had, the discussions around data modeling and taxonomies that reflect and reinscribe colonial violence. I think it's something that partly because a lot of the structured data that we are importing into Wikimedia projects, especially on Commons as well as Wikidata is using data sets from colonial institutions, namely museums and other types of institutions that have been established to categorize people and cultures. And often that categorization comes with the colonial violence of alienation and disenfranchisement. So being, as I said, that is something that is perhaps that pain that comes along with confronting those realities of the data sets as we come across them is something that is perhaps more difficult to communicate through the reports and other documentation of the events. And then finally, always as I'm thinking through these things, Marianna's presentation concluded with emphasizing the need for plurality and plurality and creativity really in how we think about the data sets that we work with on Wikidata and on Commons. And when I think and speak about plurality, I'm thinking not only about the language that we use, not only about the semantics of the machine readable data, but also about the kind of ontological structures that underline and that undergird the databases as well. Currently, in my opinion, Wikidata is imposing the ontological structure of a Western encyclopedia, but there is a potential for more plurality, more multi-vocality on a database like Wikidata. But perhaps there is scope to do some more experimentation in thinking about how linked data can provide or work towards having these multiple or pluralistic views of the world and of being in the world. There was a really interesting conversation as well in the Wikidata conference about the potentials of using decolonial English as an alternative language option. Again, because so much of that taxonomical classifications and language are language violence understanding that has been inscribed and imposed by colonial violence. So these are just some potentials or perhaps unfulfilled potential that is ahead of us as we're thinking about ways in which to bring in more ethical considerations into structured data in the Wikimedia projects. Thank you, Kelly. And I think that maybe this connect with a question we we have in the chat about by Jan about which data are you talking about access and control of if we are talking about Wikidata. We are talking in general, Wikidata is a reference, of course, here is one of the projects that we are thinking when we talk about structured data, but there are other projects too. And even interconnected with Wikidata for instance through and even Wikibase is another project we can also do the same question. I just remember the chat yesterday by Elwin one man about which have the using of Wikibase for Kitra base and those are, this is a small project but it's connected with another big project. So we are we are talking about different projects that can be interconnected. And one when we talk about access and control, we are talking about different configurations. For instance, Wikidata is a cloud source database controlled by the community with the almost the same rules we know and we practice on the Wikimedia community. And this is a but even when this is a community organizer and community led anyway, a structure of power and privileges that are that are previous of the creation and the management of the databases itself are influencing the process. So when we talk about access and control, we are talking about access to tools for using this database knowledge on how to use it knowledge on how to create new things based on this on this data and these tools. So control and access are the meaning of control and access is broader and is it is beyond the data infrastructure itself and is rooted in a strict social structures of power and privileges that influence the whole process. And that's more or less the hours that our understanding of of this issue. And I see other questions. Will you share your thoughts on what we as individual Wikimedia's affiliates and content uploaders could do to work on this important issue. Thanks, Michelle. And this is a question for for you and for everybody in this session for people that is listening. And so please, this is our question for you. And we will love to see your your suggestions, your thoughts, your ideas in the chat or in the other part. And another question by Jan. What can shoot Wikidata editors and don't do a mass import batches regular editing do different better when they get back to editing after Wikimedia. That's another super important question. And we really would love to hear from you from your perspectives. And this is an invitation also to create more spaces and more opportunities for continue the conversation. And let me share my screen one. The question is, what is next, because we started the conversation in October last year. And of course, this this questions and these problems exist before this conference and the session of October. So, one of the main conclusion was that we need more need to create and convene more opportunities to radically reimagine and redesign the internet structure data through a feminist anti colonial and anti racist lens. And for that we need more. So that's the question for you. In the Wikimedia community for for us, for everybody, what one what come and we do as Wikimedia and what would you like to see happen next to move from conversation to action. And how would you like to contribute in different ways. So please, if you have talk, if you have links, if you have resources, and if you know more conferences and spaces in which we can continue the conversation and go deeper in the conversation, please share because this is something that it reminds open for for us and for everybody in this in this conversation. So we are looking for ways to imagine radical possibilities to stay connected around these topics to make concrete steps towards emancipatory emancipatory practices in the structure of data and to join more collective spaces and to connect even small or individual projects to other projects and to create a space for for this conversation and a space for practice and as Kelly said for experimentation to So if you wish to read more to learn more, you can download the report of the of the session in whose knowledge web page, the colonizing the internet structure the data so many reports is available in English in Spanish and Portuguese so far. And you can see there is the faces of the diverse participants that joined the that first that and open conversation. So let me see if there are more comments on our questions. And to my colleague. The questions or comments, please feel free. Kelly, I am just looking to the chat. Mariana, I think Ian had a question earlier on and if there's time to at least address address it and also to say I will be in and hopefully some of the other panelists will join me in the networking session for 10 minutes or so after this session. So you can join us or join me and hopefully some of the panelists will also be there to talk a bit more. So Ian was asking, can you say a little bit more about decolonial English and arguably this could be decolonial any language. And so this is the issue that, for example, the way that the kind of taxonomies, the taxonomic language around nationhood and citizenship works on wiki data, both the language and the data modeling as far as I can tell, resists the complicated ways in which nationality, citizenship, tribal citizenship can be expressed or even ethnicity can be expressed as well. So some examples for that is in, you know, is it are we calling North America Turtle Island, or are we calling it America, are we calling the people of the Navajo Nation Navajo, or does wiki data identify that they call themselves Dine. Are we are we labeling someone as a as an object as a slave, or you recognizing that they're in a enslaved status that is there, the social and legal status. So these are just some examples, and I'm sure there are many others. And how do we, how do we model that in the data, but also then how does how do the ways that the language is modeled on wiki data reflects that there are these differences between this kind of conventional but colonial way of classifying and ordering people, and how people themselves identify in the language that they use. So hopefully that's giving you a bit more of an insight into the conversations that would be had around the colonial English but it could be the colonial any language for that matter. Thank you Kelly. And there is another question, or maybe you address this Kelly, can you share some specific example of the data structures. We should try to change. I don't know if any of you want to add more about this about more examples, but I think that it is about to recognize to acknowledge that there are not only different sources of knowledge and not only it's about to think on different communities, as a sources of knowledge to complete the lack of knowledge or the biases we have, but this conversation is also about the ontologies. And this is information science, but this is only the philosophy, the philosophical systems that in which different data sets are based on and for instance, and it is also about the relationship between the different entities. Let's say people, places, objects, and so on. And in different territories, for different people, for different communities, there are different ontologies. And I think that we need to deconstruct the idea that there is one big or ontology with a higher hierarchy that can dominate every ontology. And on the contrary, isn't how those different ontologies can talk and can interact in a transformative way, not only co-exist as separate things, but also is about if we can create this space for a conversation about there is no one, not only dominated ontology, we can move forward to a transformation, to a transformative way of doing structured data with a lot of potential also for knowledge justice and for justice itself. So I think that we don't have more time. And so thank you everybody and I hope we can continue the conversation in many match opportunities. Bye bye. Thank you everyone. Bye.