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Create documentation about your research data


Documentation provides context to understand and use your data. Imagine you want to restart a research project after several months (or years!) have lapsed. Having robust documentation will make it easier for you to do so. Without it, you may not be able to re-use or replicate your previous data.


Documentation can take many forms including:

  • Methods sections
  • ReadMe.txt files
  • Research notes
  • Code books
  • Lab notebooks


Best Practices for creating documentation: 

  • Create a procedure for creating documentation for your data. The type of documentation needed and how to capture it is dependent on the research project.

  • Ideally, you should plan your documentation procedures before starting your research project.

  • Documentation should provide as much context as possible. In general, record the who, what, when, where, why and how relating to the data. Don't forget to document abbreviations, important names/locations, data processing steps, etc.

  • Your documentation should be safely stored along with your research data. See Storing & backing up your data for more info.

  • Most importantly: be consistent with your documentation practices. Consistency is key to ensuring that your data is usable in the future!  


Organize and store your data


Created by Name / Updated on March 17, 2017 by Name

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