Bridging contributor's knowledge and the technology of The Turing Way, an open guide for data science
Jim Madge
The Turing Way/Alan Turing Institute
A personal perspective on the interface of infrastructure and people
What are we trying to achieve?
We are making something for a purpose.
How do we measure progress?
We need contributions.
Is facilitating contributors the most important activity?
Setting the scene
The problem
What we do
Lessons
The Turing Way
Me
Setting the scene
The problem
What we do
Lessons
Maintaining quality
Diverse contributors
In The Turing Way
Very diverse community.
Contributions are mostly prose.
Generally not software engineers.
Everyone can make valuable contributions and technical skills is not a measure of a contributors worth.
Setting the scene
The problem
What we do
Lessons
Why Git and GitHub anyway?
Metatext
Recognising all contributions
Support
Even more support
CI and automation
Setting the scene
The problem
What we do
Lessons
Building a community takes effort
Know your contributors
Trust in CI
Version control is not optional
Be flexible …
But know when to be strict
- Don't knowingly break CI.
- Don't knowingly introduce bugs.
- Don't introduce problems which you expect someone else to fix.
Acknowledgements
Alexandra Araujo Alvarez and Anne Lee Steele (Project and Community Managers)
Scriberia, who we work with to make the excellent, openly licensed, illustrations
All Turing Way team members and contributors!