- Understand the four facets of reproducibility.
- Be able to apply the four facets of reproducibility to improve and create more efficient and productive scientific workflows
Estimated Time: 1-2 hours
Intro to Reproducibility: Review First
Please review the material below to prepare for class.
Special Thanks: This presentation was adapted from the reproducible science curriculum. Special thanks go out to: Francois Michonneau, Hilmar Lapp, Karen Cranston, Jenny Bryan, and others who contributed to creating this presentation.
You are in a lab and a colleague has moved on to a new job and left you their research which you are tasked by your supervisor with picking up and moving forward. Have a look at the files that were left for you to work with and answer the following questions:
- Are the contents of the directory easy to understand?
- Do you feel confident that you can easily recreate the workflow associated with the data / code?
- Do you have access to the data? What data are available and where / how were they collected?
Next, work with your group to document ways in which you could improve upon the reproducibility of this project.
- Create a list of things that would make the working directory easier to work with.
- Break that list into general “areas” / categories of reproducibility.
- Hadley Wickham’s Style Guide
- BLOG: Bad vs Good Code Naming Conventions
- BOOK: Clean Code: A Handbook of Agile Software Craftsmanship 1st Edition
- Peng (2011) - Reproducible Research in Computational Science
- Markowetz (2015) - Five selfish reasons to work reproducibly
- Wicherts (2011) - Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results
- Marwick (2016) - Computational Reproducibility in Archaeological Research: Basic Principles and a Case Study of Their Implementation