Describing Data
Describing your data helps you and others to understand it in the future. Learn more about metadata standards and providing context for your research data.
Metadata Standards
Selecting a metadata standard or schema does not compel you to use it to its fullest extent. You can use as much (or as little) as you need. To search for more metadata standards by subject or scheme name, see the Metadata Standards Catalog from the Research Data Alliance.
Documentation and README files
Documentation of your data should include information such as:
- Title of dataset, investigator names, creation date, and keywords
- Purpose of study, research questions, and hypotheses
- Sampling techniques, methodology, and experimental protocols
- Equipment/instrument settings
- Description of independent and dependent variables
- Software syntax and code
- File formats, content, size, and relationship among files
- Data identifiers (DOI, URI)
- Data source, provenance, and copyright permissions
- Associated presentations/manuscripts/articles
This information can be included in the metadata that describes your files, or in supplemental files you maintain with your dataset, such as a codebook, data dictionary, or syntax files with code to replicate your process.
README files
README files are another option to document your data. This typically takes the form of a plain text file that provides context for the data collection. Cornell University's Research Data Management Service Group has a helpful Guide to writing “readme” style metadata to go with your data, including a sample README file template.