A crucial part of making data user-friendly, shareable and with long-lasting usability is to ensure they can be understood and interpreted by any user. This requires clear data description, annotation, contextual information and documentation.
Data documentation explains how data were created or digitized, what data mean, what their content and structure are, and any manipulations that may have taken place. It ensures that data can be understood during research projects, that researchers continue to understand data in the longer term and that re-users of data are able to interpret the data. Good documentation is also vital for successful data preservation.
Creating comprehensive data documentation is easiest when begun at the onset of a project and continued throughout the research. It should be considered as part of best practice in creating, organizing and managing data.
Good documentation for research data contains both study-level information about the research and data creation, as well as descriptions and annotations at the variable, data item or data file level.
Metadata are typically used for resource discovery, providing searchable information that helps users to find existing data, as a bibliographic record for citation, or for online data browsing.
Adapted from the UK Data Archive