 Hello, everyone. Today, we are seeing biodiversity from Wikimedia to Africa. My name is Abba Agnes-Ajima from Abuja, Nigeria, and we are glad to be presenting Processing Biodiversity in Africa. I'm a member of the Igbo Wikimedia User Group, an eco-founder of Igala Wikimedia. So I'm here with my co-presenter. Yes, my name is Salamat Kamal Jinn Fuseni. I go with the user named Dianne Chitro. I am with the Aguano Wikimedia User Group and a colleague for the Guramev Wikimedia community. I'm also a member of the Wikimedia Africa. Nice meeting you all. Sayamu Gid. Yes, my name is Sussin Mugi Sussuni. I go by the user name Sayamu Gid. I am the social media manager for the bunny Wikimedia User Group based in Ghana, specifically, Tamil. Today, our presentation will be on biodiversity in underrepresented languages using crowd sourcing. Wikimedia Africa, who we are and what is it about. So when you look at Wikimedia Africa program is designed to help new and inexperienced developers, programmers and technical writers in the African communities to make edits on Wikimedia projects. Also, many test Africans on building and maintaining Wikimedia tools and products by pairing them with African Wikimedians with more experience to writers or contributors. So you can learn more about us at the link below. So thank you for the wonderful introduction. So our workflow. So basically our workflow is that we do observation we observe on forum field and as a plant and animal. We upload our work on an I know Charlie's platform, which we take to, we now uploaded to Wikidata, Wikicom and Wikimedia. And this basically is done through the I naturalist. That is an I naturalist platform. So like we have here, we collect nature through the I naturalist yes, which is free and open for everyone. Then we collect our observation in an I naturalist platform project. We are opportune to have a project on I naturalist which is called the Wikimedia Africa data connection. Then we use them to put some moods book to do Wikimedia stuff in that money in digital evil. So this is the link to the stop maker that we used to make. So basically the essence of a credit stop in that money in digital evil because they are on that we are the broader diversity in Sub Sahara Africa Africa in general. It's limited. It's we have on the representation of that. So that's why we do that. That's the major work we do that as a part of the projects we do so that anybody can stop on to it and try to create a Wikipedia article. Wikidata on it. So we have this basically like a representation of the map. So if you look at African representation very well, they are more of a if you can see the dotted red, red, red part in the map. In other map of the other continent, we can see that there are more representation on Africa. Africa is most content than any other place. So we are trying to do more. Do more over observation so we can get more representation on Wikipedia and other Wikimedia project. So this is the for here we have a problem with right that the knowledge on biodiversity Wikipedia is only distributed like I explained earlier across different languages. So Wikidata contains an approximately 3.5 million that as a January 2022. Wikidata items on sites as which it means to have the Swedish Wikipedia and where I also can see we can see the people which are there. We have the Dutch Wikipedia, which is a number 11. Then we have the Benznamese Wikipedia. We have the English Wikipedia, which is more than 20,000. Then we have the Spanish Wikipedia. Then we have the Minna and Google. We have the French Wikipedia. We have the Indonesian Wikipedia. So coming down to African Wikipedia, which is what we are particular about. For the rest of what we showed before, we can see there are more representation when compared to other continents, other languages. There are more representations than the African languages. So here we have the African Wikipedia, which is a language in Africa. We have 16,000 represented by the vast representation. Then we have the Swahili, which is more than 55. But then also Wikipedia, which is in Nigeria. We have the 265, we have all the vast representation. We have the Bambara Wikipedia, which is more than 50,000. We have the Ambarari Wikipedia, which is more than 60,000. We have the Wikipedia from Ghana, in the language in Ghana, which is more than 46,000. We have the Yoruba Wikipedia, which is also in Nigeria. That's more than 66,000. We have the Malatasi Wikipedia, everywhere Wikipedia. Then finally, the Igbo Wikipedia, which has the representation of the vast diversity in Nigeria. So over to you. Yes, thank you so much for giving us the workflow. Now let's look at how to get the data on to iNaturalis. We've been hearing iNaturalis. iNaturalis is an open source platform, mobile application that is found on the Android Play Store and also the App Store on iOS. It is a free to download application. You can get to sign up if you don't have an account. If you have an account, you can get to sign in or sign in with a third party applications like your email address and other platforms. What basically we do with iNaturalis is to capture biodiversity information on flora and fauna. That's plants and animals. And if you look at the picture carefully, you'll find a lady with a camera trying to capture something from afar. There's a gentleman also kneeling before a flower to take a picture of that particular flower. Now when you capture this with the iNaturalis app, the geocodeness of these biodiversity structures, be it the plants or that tree or the bird on that tree. The geocodeness of the biodiversity item is taken and automatically updated on the iNaturalis app. This is compared with the global biodiversity information. Then editors like you and I come to identify, help identify these biodiversity, whether flora or fauna, that we have uploaded onto iNaturalis. Now with the Jupyter Notebook we have created, thanks to Andrea, our mentor. He has created a Jupyter Notebook. You'll be able to export the picture from iNaturalis to Wikimedia Commons if it has acceptable line instances. And based on this you can be able to create structured information on that on Commons and also on Wikidata. And then go ahead to create a Wikipedia article on that. Now this is a nice example of using the Jupyter Notebook to create an article on the English Wikipedia. We have an article on the Heba Street here for data. Now the Jupyter Notebook basically gives you the chance to add a title, a short information or a short description about the flora or fauna. And also it allows you to add an info box. Now on this info box is usually Wikidata powered. You can get to add image that is the image of the plant or the animal that you had captured from iNaturalis. That was important on Commons. And then you can also get to connect this to other external identifiers. And obviously if you look at number five, you can get to also link this up with other Wikipedia platforms in different other languages. Now let's look at the Dabani Wikipedia. This is a screenshot of an article, the same article that was created on the Dabani Wikipedia. On the Dabani Wikipedia we use the Wikidata powered info box called the data box. As you can see at number two, that is the data box. Then we have the flower or the plants there. This plant was imported from iNaturalis onto with Media Commons. And then it gives you the chance to have predefined headers. If you look at the predefined headers, there are general headers that Flora and Fauna usually have when it comes to biodiversity information. So for instance, on this article, on this article or screenshot, we have the belvo meaning types of varieties of that particular plant. We have the amphani, which is number three, telling us like the importance of this particular plant. If it was an animal, what is the important everything that exists has a purpose. And if we have not identified that does not mean they are just there for nothing. They all have very rich uses. Then we also have the karampai, which means read more. And this is where we get to add relevant links to other libraries and other resources where you can go to read more information about the Flora or Fauna. Then number five gives you links to different language Wikipedia platforms like the English Wikipedia, the Swahili Wikipedia, the Mori, the Gurini, and other Wikipedia platforms that you can get to read about that same particular plant. Now, what is the aim? Why are we doing this? Why are we concerned? Why do we think we need your own work? Because we have been editing on Wikipedia and perhaps have not taken conscious effort to look at the biodiversity information. So we are inviting everyone here who has been contributing on Wikipedia to also join us to increase biodiversity information because if we have a species that is currently not written on Wikipedia, we are not contributing to the total sum of human knowledge. We also want to increase the finability of existing knowledge on these flora and fauna. There are a lot of plants and animals species that are undiscovered up to this point. And most of them are found in indigenous communities. So we need all of you on board. Just get your iNaturalist app and then you get started. Now, we've been mentioning data box, data box. Data box is simple. It's wiki data powered. If you can still do not have that on a long way to Wikipedia, these are very simple steps you can use to be able to install the data box. If you click on the resources, you are going to find a lot of other resources. You first of all create the template or you import the template, import the module, and you are good to go. There's a video tutorial here under the resources to guide you through on how to be able to install data box. So yes, we need everybody on board. Come be an iNaturalist today and when you become an iNaturalist today, we still invite you to come and join Wikimedia Africa where we pair up talents and let people think, pair and share. And when we share everybody we use and again once we become Wikimedia Africans, then we can help identify indigenous plants and animals from indigenous communities. If you look at the iNaturalist now we have over 151 millions of iNaturalist users like people contributing. We have a lot of species. We see the numbers here. All these numbers speak for themselves. At this point, we want to say a very big thank you to Benedict Ode for being the organizer of the Wikimedia Africa and also to our mentor Andrea Wacomista. We also want to say a very big thank you to the Debanu Wikimedia itself group, the Igbo Wikimedia community, the Igbo Wikimedia itself group and also the iNaturalist community for always supporting us and getting us to discover more flora and foreign information and get to write more about them. Thank you so much for the audience and we are really grateful. If you have any questions, you can reach out to any of the presenters via our usernames or on social media and we'll be glad to access or answer any questions that we may have. Thank you so much. Bye bye. Thank you.