Theme 3 Data Documentation and Metadata
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This section contains the following questions:
- What documentation will be provided to enable understanding and reuse of the data collected/generated in this project?
- Will a metadata standard be used?
Later in this course you will learn more about data documentation. Suffice it here to say that documentation basically is any information needed to understand & reuse research data, and to reproduce your research – ideally following standards in your domain. In other words, this could be
- a codebook/data dictionary explaining variables
- a dataset structure, relation between files
- a study context
- protocols, methods, SOPs
- notes/annotations
- machine configurations
- the software used
- processing & analysis scripts
- consent information
- etc.
Ensure that it is clear what the study was about, what the variables in your data mean and what the codes mean if used. There should be no blind spots.
Metadata refers to a highly structured form of data documentation.
- Needed to search & find data (e.g. catalogues)
- Also used to further describe/annotate data
- Fixed set of elements, as defined by metadata ‘schema’
- Use existing standards!
- generic: e.g. Simple Dublin Core, Datacite
- domain-specific: check via fairsharing.org, RDA metadata directory, DCC’s list of disciplinary metadata
