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Welcome to The Turing Way project GitHub repository. This is where all the components of the project are developed, reviewed and maintained.
The Turing Way is a handbook to reproducible, ethical and collaborative data science. We involve and support a diverse community of contributors to make data science accessible, comprehensible and effective for everyone. Our goal is to provide all the information that researchers and data scientists in academia, industry and the public sector need at the start of their projects to ensure that they are easy to reproduce at the end.
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The Turing Way is a book, a community and a global collaboration.
All stakeholders, including students, researchers, software engineers, project leaders and funding teams, are encouraged to use The Turing Way to understand their roles and responsibility of reproducibility in data science. You can read the book online, contribute to the project as described in our contribution guidelines and re-use all materials (see the License).
Screenshot of The Turing Way online book (use this image in a presentation)
Started in 2019 as a lightly opinionated guide to data science, The Turing Way has since expanded into a series of guides on Reproducible Research, Project Design, Communication, Collaboration and Ethical Research. Each guide offers chapters on a range of topics covering best practices, guidance and recommendations. These chapters have been co-authored by contributors who are students, researchers, educators, community leaders, policy-makers and professionals from diverse backgrounds, lived experiences and domain knowledge.
Our moonshot goal is to make reproducibility "too easy not to do".
Table of Contents:
π§ If you prefer an audio introduction to the project, our team member Rachael presented at the Open Science Fair 2019 in Porto and her demo was recorded by the Orion podcast. The Turing Way overview starts at minute 5:13.
Reproducible research is necessary to ensure that scientific work can be trusted. Funders and publishers are beginning to require that publications include access to the underlying data and the analysis code. The goal is to ensure that all results can be independently verified and built upon in future work. This is sometimes easier said than done. Sharing these research outputs means understanding data management, library sciences, software development, and continuous integration techniques: skills that are not widely taught or expected of academic researchers and data scientists. As these activities are not commonly taught, we recognise that the burden of requirement and new skill acquisition can be intimidating to individuals who are new to this world. The Turing Way is a handbook to support students, their supervisors, funders and journal editors in ensuring that reproducible data science is "too easy not to do" even for people who have never worked in this way before. It will include training material on version control, analysis testing, and open and transparent communication with future users, and build on Turing Institute case studies and workshops. This project is openly developed and any and all questions, comments and recommendations are welcome at our GitHub repository: https://github.com/alan-turing-institute/the-turing-way.
The Turing Way is an open collaboration and community-driven project. Everyone who contributes to this book, no matter how small or big their contributions are, is recognised in this project as a contributor and a community member. Long-term contributors of the project are considered part of the core contributors groups who take on various leadership roles in the project.
The project is coordinated by the lead investigators Kirstie Whitaker (founder) and Malvika Sharan (community developer) and hosted at The Alan Turing Institute.
You can read The Turing Way acknowledgement process and Record of Contributions to learn about how we acknowledge your work and how our contributors are highlighted in the project. Please see the Contributors Table for the GitHub profiles of all our contributors.
π§ This repository is always a work in progress and everyone is encouraged to help us build something that is useful to the many. π§
Everyone who joins the project is expected to follow our code of conduct and to check out our contributing guidelines for more information on how to get started. We want to meet our contributors where they are. Therefore, we provide multiple entry points for you to contribute based on your interest, availability or skill requirements.
Contributions include development and sharing of new chapters; maintenance and improvement of existing chapters; sharing The Turing Way resources; review and updating of previously developed materials; translating its chapter to help make this project globally accessible, and sharing best practices in research.
Community members are provided with opportunities to learn new skills, share their ideas and collaborate with others. They are also given mentorship opportunities in the project as they make their contributions to The Turing Way or other open source projects and are encouraged to mentor new participants of the project.
We have created a promotion pack to help you in presenting and sharing about The Turing Way in your network.
You can reference The Turing Way through the project's Zenodo archive using DOI: 10.5281/zenodo.3233853. DOIs allow us to archive the repository and they are really valuable to ensure that the work is tracked in academic publications.
The citation will look something like this:
The Turing Way Community, Becky Arnold, Louise Bowler, Sarah Gibson, Patricia Herterich, Rosie Higman, β¦ Kirstie Whitaker. (2019, March 25). The Turing Way: A Handbook for Reproducible Data Science (Version v0.0.4). Zenodo. http://doi.org/10.5281/zenodo.3233986
You can also share the human-readable URL to a page in the book, for example, https://the-turing-way.netlify.com/reproducibility/03/definitions.html, but be aware that the project is under development and therefore these links may change over time. You might want to include a web archive link such as https://web.archive.org/web/20191030093753/https://the-turing-way.netlify.com/reproducibility/03/definitions.html to make sure that you don't end up with broken links everywhere!
We really appreciate any references that you make to The Turing Way project in your and we hope it is useful. If you have any questions please get in touch.
The Turing Way illustrations are created by artists from Scriberia as part of The Turing Way book dashes in Manchester on 17 May 2019, and London on 28 May 2019 and 21 February 2020. They depict a variety of content from the handbook, collaborative efforts in the community and The Turing Way project in general. These illustrations are available on Zenodo (https://zenodo.org/record/3695300) under a CC-BY license.
When using any of the images, please include the following attribution:
This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence.
The latest version from Zenodo can be cited as:
The Turing Way Community, & Scriberia. (2020, March 3). Illustrations from the Turing Way book dashes. Zenodo. http://doi.org/10.5281/zenodo.3695300
We have used a few of these illustrations in the Welcome Bot's responses to new members' contributions in this GitHub repository.
You can contact The Turing Way team by emailing theturingway@gmail.com.
You can also contact Malvika Sharan by emailing msharan@turing.ac.uk or Kirstie Whitaker by emailing kwhitaker@turing.ac.uk.
Connect with others and discuss your ideas on Slack using this invitation link.
We also have a Gitter chat room (if you prefer an open source alternative for chat) and we'd love for you to swing by to say hello at https://gitter.im/alan-turing-institute/the-turing-way. The room is also accessible with a Matrix account at #alan-turing-institute_the-turing-way:gitter.im.
We have a tinyletter mailing list to which we send monthly project updates. Subscribe at https://tinyletter.com/TuringWay.
You can also follow us on Twitter (@turingway).
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind welcome!