Research Data Management: Data Documentation

Providing documentation for your research data will help you, your team, and other researchers understand your data. This is beneficial for others who may want to use your research data in the future in order to advance scientific progression.

There are a few different ways to document your data, including in laboratory notebooks, ReadMe files, and using a metadata schema.

Things to include when documenting your data are:

• Data dictionary (define variables, abbreviations, acronyms)
• Data location
• File organization system
• Process and workflow (how your data was cleaned, software or coding used in analysis, etc.)
• Metadata (see below)

Metadata is "data about data", or in other words, how would you describe your data? There are several different metadata standards that provide a template of what kind of information should be provided in order to describe your data and make it discoverable. Commons metadata elements include creator, date, format, description, and more.

General Metadata Standards

• One of the most widely used metadata standards is Dublin Core due to its general metadata elements that can be used for many different subject fields and resources.

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