Last updated on 2023-08-31 | Edit this page

This page has a collection of resources on good practices in scientific computing. Feel free to refer to them.

Some other lessons with different emphasis

The FAIR principles describe work that is Findable, Accessible, Interoperable and Reusable.

These lessons are in a similar format and discuss good practices within the FAIR principles:

Further Carpentries lessons

Many other Carpentries lessons may help further your learning:

Papers and sites on open and good practices

Ten simple rules for reproducible computational research

  • Keep Track of How Every Result Was Produced
  • Avoid Manual Data Manipulation Steps
  • Track Versions of All External Programs Used
  • Version Control Your Protocols/Scripts
  • Record All Intermediate Results
  • Track Relevant Sources of Randomness
  • Store Raw Data behind Plots
  • Allow Layers of Detail to Be Inspected
  • Connect Statements to Underlying Results
  • Share Scripts, Runs, and Results

After Geir Kjetil Sandve et al (2013)

Research is changing

For example,“papers” aren’t paper any more

Resources: External Training

Many institutions and societies run training courses, for example:

For more courses:

  • look at the posters on the walls around your lab
  • ask for advice!
  • talk to the head of your PhD program, postdoctoral fellows office, etc.
  • google “bioinformatics course”, etc.

An example of one institution: Resources at the University of Edinburgh