Good practices

• Use Open-Source as much as possible.

  For software and for data. A list of recommended file format can be found at https://researchdata.epfl.ch under “TOOLS –> EPFL Recommended File Formats”. This means writing script in python rather than Matlab, saving in odf or csv rathern than in xlsx format.

• Organize and describe your data.

  • Follow the recommended folder structure and naming conventions: Data organization .
  • Describe your data with sufficient metadata, use our README generator to help you create metadata faster. To see how to use it: Generate README file templates for metadata.

• Publish your data.

  • For example using zenodo or other data repositories.
  • You can also use data journals like The Journal of Physical and Chemical Reference Data.
  • Publish as much data as possible and organize it as described above.

• Write Data Management Plans for your projects.

  This is particularly important when writing research project proposals. We provide several templates and tools in the reference section to help you write a DMP.

• Check a few example on how other people do it.

  We have collected a list of examples in the references on how code or simulation data can be published. Check them out to see how other labs round the world share simulation data or code pertinent to analysis of this data: References and useful links