 Welcome everybody. I am Malvika Sharan. I am here with my colleagues Mellie and Esther and we're representing the Turingway. So the Turingway, it's a community-led guide on data science. It used to be a guide but it's a project now with a lot of different wing pieces. We are open source, open collaboration and community-driven project which works with a distributed community to build whatever we can to make data science accessible, reproducible and beneficial. There are four main areas that I hope we are able to highlight today. So we have co-created a book and that book is always a work in progress. It's a book which is online. You have to come in and tell us what we can do better. If there is something from your work that is missing that should be highlighted, we are very, very happy to have that facilitated. But it is a community based resource which means community decides what is important for them. We are building a global recommendations and guidelines and if we cannot do it, if we don't have representation from global community. And we built on participatory process and we are working towards culture change and culture change in the sense that we want to identify the challenges that affect us and the solution that actually makes it better. So it started as a book on reproducibility. There are lots of chapters about reproducibility but it became immediately apparent that it's not just about tools and resources. It's also about how we build those tools, how do we use those tools, who is impacted as a result of using those tools. I won't be talking a lot about it because in 2019 Krstewittaker who started this project gave a fantastic talk. So please do check her out. She loves that picture because that's the first time she was able to use Binder on her computer where she pinged a link and it opened a Jupyter notebook and she was excited. And that's the excitement that we kind of see every now and then when different people come into the project, they learn about GitHub, they learn about Jupyter or Binder for the first time. So the project team, the staff members, which includes me, Scorsi and I lead this project. Anli Steel is our community manager and one of our recent addition is Alexandra Arauzo Alvarez who's our project manager. The project has existed for about four years. We have over 260 chapters, loads and loads of resources and the project has expanded from just being a guide on reproducibility to being a series of guides on different things that affect reproducibility, including guides for project design, communication, collaboration, ethical research, as well as community practices. So all these resources, of course, we haven't written all of them. We work with the global community. At this point we have over 430 people who have co-authored the chapters and we owe it to them. These chapters are also always evolving because data science practices are evolving so we don't believe that this book will ever finish. So if you get overwhelmed by how big the book is, just so you know it's not complete. So as I said, we have a lot of co-authors. We have loads and loads of uptake from the project. We have also been able to engage with lots of communities all around the world, learn from them, share knowledges with them. We are peer-reviewed articles but we are not a traditional book. We are community resource book. However, we also manage it through community-led review system and we have been used in lots of policies. However, none of those policies have been written by us. The project has been extended and replicated by other organizations and other projects and that's our purpose. We build CC by 4.0 so we want you to copy, paste, reuse, remix, do whatever you would like to do. Where everywhere, all the images we are going to use are also available for reuse. So I wanted to speed up to that part so I can come to this part to say, so don't get distracted by the name Turing in the project's name. It is not Turing Institute's resource. It's an open source project. It belongs to the community. It is always evolving with the needs of the community. We are creating community process. It's not the way but the journey that we are interested in. There are quite a lot of different ways people have built. There's not one single right or wrong but there are lots of different ideas that people brought in and they have started to lead on it and there are a couple of those which we will be highlighting today. Our purpose is to actually move towards as much as involvement, collaboration and empowerment. So I'm going to pass it to Mellie to speak about localization. Thank you, Mojica. Hi everyone. Can you all hear me? Great. So one of the ways that we work in the Turing way is what we do in the localization and translation team. We have someone from this team back in the audience too, Andrea. Well, first of all, some of the questions that spark conversation and action among us are what does an open global resource look like in the Turing way or in an open science project? How can we actually make sure that that is global participative and that we're doing inclusive open science? Are you able to do that in your own project? How do you do that? So we have been asking ourselves these questions and trying to come up with ideas on how to work together with people from multiple geographies and how could the Turing way than being a book, a community and many other things be this global resource for researchers from all over the world or just curious people, interested people in open science and in data reproducibility. So this map by Juan Pablo Perín, a local researcher, showcases visually this drastic difference in the participation in knowledge production between what's called by a few people, the global north and the global south. That shows, let's say, who can participate in this conversation with their own voices because in the current system we have to be able to speak up in science. In many cases you need to publish a paper, you need to publish a book, but it's clearly not the same for depending where you are in the world. So based on this UNESCO recommendation for open science practices and on many scholars, we've been trying to discuss how language is actually a matter of accessibility and that kind of like frames the work we do at Turing way. So trying to understand that knowledge is part of our language actually is part of trying to overcome those barriers in participation in science and in open science specifically. It is a way to make our work more inclusive, it is a way to make it available for people that otherwise would be taking longer and taking a very unfair pathway to produce and to gather knowledge in their region. So how do we do this? Well, we're speaking in the realm of multilingualism and internationalization in open science. Making science open requires that we have these locally relevant resources, so that's kind of what localization is about, more than simply translating it. We're going to be talking more about this, but open science has actually a lot to learn from the communities that are invited to participate in this process during, you know, when they're able to have it in their own languages and it allows open science resources to then be more about their local identities and not about let's say something that comes from, let's say an alien resource to them. So how do we do this in the Turing way? First of all localization is not the same as translation, while translation is simply a matter of, you know, translating one word to another language without textualizing this. With localization you can actually gather information from the local community, from the local environment to make it more difficult in reality, let's say it like this. And how do we do this with a digital book like the Turing way that's, you know, hosted on GitHub? It would be really costly to do this, you know, manually. So we use these systems that are translation management systems. We have used a platform called TransEffects. We currently use another one called CrowdIn and they manage localization process by offering machine learns translations. So we can just review them and it takes time, it takes effort. We have been doing this actually for many, many years on our own. We had been doing this in a very costly way and with a project like the Turing Way Translation and the localization project we can do this collectively and automated so it's much easier. These are some of the people that contribute in the governance process of the sub-team. We thank them very much. And just so you can see what it looks like, this platform is currently being translated in all these languages that are here, Japanese, French, Arabic, Turkish, Spanish, Portuguese, many others. They're just hosted in the GitHub repo TWA translation too. And you can actually participate in many ways in many different roles. You don't need to be only a translator. You can choose your own way to be a part of this team. By being a translator, a proofreader, a manager, you know, you can work on documentation. We've had interns from outreach, for example, that worked on the documentation. And I guess this is only one of the Turing Ways. It's going to show us a little more. Yeah. So I'm going to be talking about research infrastructure roles, which you're probably going to think, what is this? But I'm going to start out with a statement that what I see in research is that successful research is not done without any facilitation, project management, maintenance work in the background. And these are all very sometimes invisible contributions, but they're there. And in the Turing Way, we have been giving these contributions or people that do these types of contributions a name for their role, research infrastructure roles. So that's what we mean with research infrastructure roles. It sounds a bit like very technical, but it's actually a very human aspect of it. And we argue that these types of roles provide specialized skills, expertise and services that are really required to have effective research, quality research. And if that is still a bit vague in the chapter that we have on these roles in the Turing Way, we have a couple of examples listed, which were actually gathered as a result from a workshop at a different conference where people gave input on these types of roles. And, well, I'm not going to name all of them. I'm just going to say Data Steward, because that's my role at the Delft University of Technology. But there's like loads of examples of these types of roles. And what is needed for these types of roles, the flourish in the research ecosystem, as what I said, it can look very invisible, our contributions, is some more recognition and actually fully partaking in this research system. And I'm also not going to read out these two examples, but we do see a movement, at least in the UK and Australia, towards recognizing that, hey, these roles are actually there. And then the second point of, okay, maybe we should also recognize their contributions. And I would actually love some input on how this works here, because so far we've been focusing on the UK, Australia, and Europe, and US. And I haven't found a lot on this in other areas of the world. So if you have any input, and if you're now thinking like, oh, I'm also doing such a role, please do reach out, because we really value your input. One of the last things I want to say about that is that we actually did a more extensive talk on this as part of CSV conference. Together with Ariel, I did a recorded talk, and that should be up on the YouTube channel whenever they put up the recordings. And you can already find a link to the pre-print on this, which is called a Manifesto for Rewarding and Recognizing Team Infrastructure Roles. And Team Infrastructure Roles is almost the same as Research Infrastructure Roles. So, and how we do this in the Turing way is actually you're part of the Turing way as a contributor, so you're not separately listed in the citation, so to say. But all of the contributions are separately tracked through the all contributor bot. And these are not just technical contributions, but also things such as reviewing or discussing community management, event planning, I think is in there somewhere. And next to that, there's also a way to more qualitatively indicate your contributions in the contributor record. So, I think the Turing way is actually one of the projects that are spearheading this type of recognizing contributions of anyone participating in a project. And if you're interested in contributing, there's many ways to do that. I think Mofica is going to go into that. Okay. So, you can develop your own page of information in the Turing way. You can review it. You can maintain it. You can fix typos, bugs. You can put a discussion, an issue into the GitHub repository, propose ideas, share your resources. We also don't want to reinvent the wheel. We're also copy and pasting and referring to other resources. So, please do share if you have anything relevant, especially if you have best practices. We would love to hear from your best practices. And if, I mean, Melly just explained the translations team and localization team work, always looking for more people. I think I see some nodding. So, yes, please join. And I think I already mentioned reviewing and updating. So, we're very, we would love to have you. So, please do have a look and join. Then I think. Yeah, I'm just going to then bring us all back as I started. There are so many things that we haven't mentioned. We don't have time, but we love to talk about it. There are many ways for us to connect. If you would go to the start page, you can find us and you can find different ways to connect with us. Please drop us an email. We're always happy to hear what you have to say and what kind of conversation we have not had. You would find exactly what kind of events in the start page. So, please forgive me for moving too fast. So, growing to Turingway as we are every year evolving and moving towards more and more broader and broader community, we are realizing the power of not defining who we are in a more strong sense. We want to create a space we're not creating solution. We want to create a welcoming and safe space where you can come together and find solution that works for you. For us, what's important is to shift our understanding of how it takes conscious effort as a grassroots community to move. We don't want to move very fast. We want to move with people. And we are also now thinking a lot about sustainability, not just in terms of open source. We shouldn't remove open source away from the climate change and environmental crisis. So, we want to learn about what does that mean in the work that we do. So, facilitating and maintaining is one of the important things that both of them have highlighted and that is definitely a core of the Turingway. So, yeah, let's not move fast and break things. Let's collaborate, move slowly and maintain things. Thank you so much for listening to us. Thanks very much. Do we have any questions in the room for the Turingway? Just raise your hand then I can come to you with the microphone. Do you have any regional leads as well who coordinate work at a country level or maybe like outside of the states, maybe different regions? We do have a lot of regional leaders, but we don't really. So, I have to say we have people from Middle East, from Latin America. We don't have anyone from India and with love for you to help us get there. And my Hindi, I studied in full Hindi until I was 15 and if you ask me to translate something, it would be very difficult. So, I'd really, really appreciate some more engagement from Asian communities. But also, I hesitated to say we have regional coordinator. I think we've been working in a very desilode way. We have not done very concentrated effort region-wise. Is that the direction we want to go? We don't know. We definitely are up for discussion. So, definitely yes and no. Yeah, just to add to that, I work at a discipline-specific repository and there we do have regional coordinators because it makes more sense because each of these countries or regions contributes different types of data sets. But for this is more like topic-based. So, I'm not necessarily coordinating research infrastructure roles. Neither is Ariel, but she did start it. So, she's a natural talk-to point. But basically anyone can come in and just take over the lead or contribute or change it. So, it's very decentralized. We haven't thought about it carefully, mostly because we're like, come here and talk to us and we love talking to you. But we never said, oh, can you go back and bring more people with you? People generally tend to do that. But I think, yeah, as Ariel is saying, it's very practice-based. I think I can add a little bit about the translation and localization team. We do have co-leads for different languages. So, this is kind of like how we came up with the governance for the subteams. And they, well, Batul, André, that's here for Portuguese, but for Arabic are two examples. And I'd say that also the localization contribution is often an entry point for other types of contributions to the turnway. It's one of the, I guess it's one of the ways that people come in most easily to the turnway as a contributor. And then, perhaps, they can start branching out to other parts of the community. And perhaps, one day, you know, start leading different efforts there, too. Unfortunately, I don't think we have time for any more questions, but I would encourage you to go and talk. But before that, just to give a big, big round of applause for the turnway.