A Summary of Research Data Documentation Methods

A phrase that often comes up when data librarians speak about documentation is that “documentation is a love letter to your future self.” Basically, documentation is necessary because research data rarely speak for themselves and researchers forget details over time; therefore documentation is necessary in order to interpret data in the future.

Different disciplines gravitate to different forms of documentation (e.g. chemists use laboratory notebooks but social scientists running surveys more often leverage codebooks) but this often means that researchers are not aware of the full scope of documentation methods beyond what is preferred within their discipline. While I’ve written a lot about documentation on this blog already, I wanted a quick way to show researchers the full range of documentation possibilities. So I developed a 2-page handout that summarizes different forms of documentation and when to use them.

The handout summarizes seven different documentation forms to expose researcher to methods that might improve their data management and work better in certain parts of their research workflow. These seven methods include:

  • Laboratory Notebook, Field Notebook, or Research Notebook
  • e-Lab Notebook (ELN)
  • README.txt
  • Templates: Data Sheet, Collection Sheet, or Field Sheet
  • Data Dictionary
  • Codebook
  • Metadata Schema, Standard, or Taxonomy

I’ve blogged about most of these documentation types in more detail, but I hope it’s helpful to be able to review them all in one place.

Please do check out the new documentation handout and feel free to reuse it – it’s licensed under a Creative Commons Attribution (CC BY) license, meaning you are welcome to use and remix it so long as you credit me. And thank you to Tom Morrell and Megan O’Donnell, who reviewed earlier version of this handout and suggested improvements.

I hope this new resource is helpful to you all!