Metadata
Metadata is structured "data about data" that is also citable and machine-readable (e.g.: DOI persistent identifier, date of publication, title, author, description, keywords, licence, etc.). Data with rich metadata are more likely to be found and reused in the future.
General metadata standards (e.g. Dublin Core) or domain-specific standards (e.g. DDI) can be used. Metadata standards and domain-specific policies directories:
Documentation
"What information is needed to be able to read and understand the data in the future?"
Additional documentation helps users of our data to understand and re-use the data.
Examples of supporting documentation:
- laboratory logs and protocol descriptions
- Questionnaires
- code lists, variable definitions, data dictionaries
- Units of measurement
- ontologies, controlled vocabularies
- programming language syntax and software output files
- information on equipment settings and instrument calibration
- database schema, description of file directory structure, naming structure
- reports on methodology
- information on analysis and procedures
- information on the origin of the data extracted or digitised
- software code - does it need to be kept for data reproducibility?
Example of a README.txt template: https://cornell.app.box.com/v/ReadmeTemplate