Skip to main content

Data description

Ensure that everyone can understand your research data

Describing your data is essential in ensuring that you, and others who may need to use your data, can make sense of your data and understand the processes that have been followed in the collection, processing and analysis of your data.

Data documentation

You should document everything that you or another researcher would need to make sense of your data in the future. Some storage systems provide mechanisms for you to do this when you save your data. In other storage systems you may have to document your data manually in README documents or version control tables.

A README document is a plain text document that’s stored alongside and describes your data. Details to include in a README are:

  • file naming conventions
  • data definitions, e.g. definitions of variables or row and column headings
  • units of measurement
  • how different files relate to one another
  • explanation of data processing steps
  • software or tools used to create or read the files


The descriptive information about your data is known as metadata. Many computer systems also create additional technical metadata about your files. All of this metadata is useful for understanding, managing, and preserving your data effectively and makes your data more findable and usable to other researchers if the data is published or shared.

Some fields of research have developed specific metadata schemas that set out the types of information about your data that should be documented. If you’re working with large datasets, databases, or data management systems, then you should contact the Research Data team for advice on metadata schemas that might be appropriate for your area of research.