MetadataThe term metadata is commonly defined as "data about data". In other words, metadata refers to information which describes or provides essential context to understanding data.
Using a metadata standard (i.e. filling out a required set of fields) as part of your research data management strategy will help ensure that data is documented and structured consistently. In turn, this will further ensure that your data is not only understood over time by yourself and research team but by other researchers. Using a metadata standard also makes it easier for others to discover your data for re-use after it is deposited with a trusted data repository for long term preservation.
Metadata standards can be general (multidisciplinary) as well as discipline specific. A comprehensive list of metadata data standards and tools can be found here.
DocumentationDocumentation, a form of metadata, also refers to information about data, and when it is very structured it can be considered metadata. The importance of metadata lies in the potential for machine-to-machine interoperability, which provides added functionality, or 'actionable' information.
Research data can and should be documented at various levels.
1. Project or Study level documentation refers to information which describes how research data was collected and processed.
Specific considerations include:
- study purpose
- how the study contributes to new domain knowledge
- what the research questions/hypotheses were
- methodologies used
- sampling frames were used, what instruments and measures were used
3. Variable level documentation includes a full description of variables, including the full name of a variable (versus its associated label in a spreadsheet), its response options and how the variable was operationalized (conceptually defined).