The Turing Way: An open source community-driven online book about reproducible, ethical, inclusive and collaborative data science.
The Turing Way started in December 2018 and has quickly evolved into a collaborative, inclusive and international endeavor with the aim of uncovering gold standards to ensure reproducible, ethical, inclusive and collaborative data science. How did this happen? I think two ingredients were central to The Turing Way‘s success: extraordinary community building and a clear enticing vision.
Anyone can contribute is a central theme. And not only that: anyone can bring ideas to the table. And folks are doing just that. At the time of writing this post 168 people have contributed. So on average the project has gained 9 new contributors every month since it’s initiation.
The extensive contributing guidelines, the biweekly collaboration cafes, and other events help people getting started. The Code of Conduct helps everyone feel safe. All kinds of contributions are valued (for details see the all contributors specification). I joined The Turing Way at a book dash: a two day event where a room full of motivated contributors focus on improving the book and adding new content. It was a wonderful experience! Kirstie Whitaker and Malvika Sharan managed to create such a friendly and welcoming environment; It made working in that room in the Turing Institute with all the other contributors a blast.
For collaborating on the material, we use GitHub. The “rules” are simple:
- New idea = open an issue
- New content = start a pull request
If you don’t yet feel comfortable working with GitHub, the community will help you get up to speed – for example in one of the collaboration cafes. It’s that simple. Before you know it you helped fix the first typos and have written the first chapter.
I did not know the initial reasons for the mode of development of The Turing Way. So I asked Kirstie Whitaker, the founder. She says:
There are three answers to this question. One is that openness is a political act of justice and empowerment. Disseminating knowledge is not a capitalistic activity: I am not lessened by sharing information whose generation and synthesis was funded by the UK tax payer. The second is that I believe in the power and creativity of diverse groups. A community-created resource will be better and more effective than one developed by “me” or “my team”. Finally, writing the book together under an open source license supports its scalability. The Turing Way can only achieve its hugely ambitious goals of making reproducible research “too easy not to do” if we all work together to use, re-use, remix and refine the content for specific use cases across all aspects of data intensive research.
I think there is a lot we can learn from projects like The Turing Way. I will definitely take some ideas from the project and implement them in other projects and communities. Let me try to summarize the most important points:
- Publishing does not need to be a commercial endeavor. It can be free for both authors and readers.
- Use the power of the internet for publishing! No need to print everything on paper.
- Together we can achieve more – if we organise it well.
- A clear enticing vision can go a long way.
- Value all contributions and acknowledge them fairly.
The book: https://the-turing-way.netlify.app
The GitHub repository: https://github.com/alan-turing-institute/the-turing-way
Cite as: A Community Handbook for Open Data Science, Heidi Seibold, published 2020 via Generation Research https://doi.org/10.25815/b7zg-nf66
All images in this story created by Scriberia for The Turing Way community and used under a CC-BY licence.