The Turing Way
1. Introduction
2. Reproducibility
2.1 Why reproducibility is important
2.2 Why you should care
2.3 Definitions
2.4 Resources
3. Open Research
3.1 Open data
3.2 Open source software
3.3 Open hardware
3.4 Open access
3.5 Open notebooks
3.6 Open scholarship
3.7 Resources
4. Version Control
5. Licensing
5.1 Software licenses
5.2 Data licenses
6. Collaborating on GitHub/GitLab
6.1 README and Project Communication
6.2 Roadmapping
6.3 Getting Contributors
6.4 Checklist and Bibliography
7. Credit for reproducible research
8. Research Data Management
8.1 The FAIR principles and practices
8.2 Storage and backup
8.3 Data organisation in spreadsheets
8.4 Documentation and metadata
8.5 Sharing and archiving data
8.6 Personal Stories
8.7 Resources
9. Reproducible Environments
9.1 Choosing a tool
9.2 Conda
9.3 YAML
9.4 Binder
9.5 Virtual machines
9.6 Containers
9.7 Checklist
9.8 Resources
10. Code quality
11. Testing
12. Reviewing
12.1 How this will help you and why this is useful
12.2 Best Practice
12.3 Typical Workflows
12.4 Checklists, what to learn next and bibliography
13. Continuous Integration
14. Reproducible Research with Make
15. Research Compendia
16. Risk Assessment
16.1 Long Read on Risk Assessment
16.2 Summary
17. BinderHub
18. Glossary
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