The Turing Way: A how to guide for reproducible research
summary
The Turing Way claims a practical, community‑authored handbook that reduces reproducible research to concrete steps: version control workflows, automated tests and continuous analysis, and runnable environments via Binder that rebuild notebooks in browsers. It supplies runnable examples, a Makefile-driven paper, and checklists; metrics target 50 first pull requests and tracked contributor pathways. The project is live, open source, uses Jupyter/Travis/GitHub tooling, and demonstrably runs and updates analyses end‑to‑end.
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chapters (19)
- 0:00Welcome to The Turing Way
- 1:57Reproducibility in research
- 4:25Human barriers to reproducibility
- 7:32Automating workflows
- 9:41Turing Institute’s role
- 11:06What is The Turing Way
- 13:32Testing academic code
- 15:17Continuous analysis workflows
- 18:07Prerequisites for continuous integration
- 19:50Version control barriers
- 21:38Book dashes and collaboration
- 22:21Binder for reproducibility
- 24:50Binder benefits for reviewers
- 26:39Custom Binder hubs
- 27:47System differences and results
- 28:52CSV errors in data science
- 30:16Open science principles
- 31:42Contributing to The Turing Way
- 32:44Project success metrics
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