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Scripting

The 5 Do's of open science scripting

The following are meant as a set of guidelines for you to consider adopting in your scripting. We don't expect people to adopt all of these points instantly. Perhaps try adopting one point at a time.

  • Do make your code available on GitHub (or similar) platforms even if it doesn't run top to bottom
    • As academics, being able to share our code is actually a privilege - make use of it - and admittedly it may not always feel like it!
    • Too often "my code doesn't run" is used as an excuse not to put code online
    • You don't have to know how to use Git in order to use GitHub - drag and drop files into a repository using GitHub's web interface
  • Do document your code
    • "Your closest collaborator is you from 6 months ago, and they don't answer emails". Documenting your code through README documents and in-line comments is a way of being transparent about what your code does, and a way of being kind to yourself!
  • Do learn dynamic documents e.g. R Markdown / Quarto / Jupyter notebooks
    • A clue you could find them helpful is if you find yourself inventing your own comment syntax for headings in your scripts
    • It makes it really easy to share analysis with others and to iterate through versions without having to copy and paste output into Word documents for example
  • Do consider separating your code from your data and output
    • Using config files to store absolute file paths means that your code reads in the location of the data (example)
    • It helps prevent accidentally sharing sensitive data when you share your code (e.g. on public spaces like github)
    • This can help with accessing RDSF locally and on HPC
    • It's a good security practice to avoid sharing file paths publicly
    • It makes it much easier to run your code in different locations, because the config file can be different in each location depending on where to find your data and outputs
  • Do constantly keep learning and trying to improve your coding
    • One way to do this is to read code on publicly available GitHub repositories
    • Have a look at papers such as Wilson et al., Best Practices for Scientific Computing, PLOS Biology, 2014 DOI
    • and Wilson et al., PLOS Computational Biology, 2017 DOI
    • and the Reproducible Research section of the Turing Way here
    • and Morton et al., BMJ Health & Care Informatics, 2022, 29:e100488 URL

Monthly meetings

Leads: Matthew Suderman

We'll hold meetings in OS6 at Oakfield House every first Tuesday of the month at 12pm, lunch will be provided! Sessions are themed and will be recorded

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