Metadata Standards

Properly describing and documenting data allows users (yourself included) to understand and track important details of the work. Standardization enables interoperability between systems, and greatly increases the ability of others to find and understand your data, and know what the requirements are for access re-use. It enables your data to be connected to relevant resources, such as publications, citations, indexes, measures of impact, and grants.

Metadata can take many different forms, from free text in a readme file to standardized, structured, and machine-readable information that follows a metadata schema.

Which metadata schema should you use?

Data centers and repositories may use certain metadata standards and require a minimum set of information to accompany data. Check with the repository where you might deposit your data before you begin outlining the metadata information in your data management plan.

Some repositories provide metadata assistance and other data curation support to data depositors, either free or for a fee (e.g., Inter-university Consortium for Political and Social Research – ICPSR).

If a standard has not been defined for your discipline or you’re not sure what repository you will use, contact

For a general data-centric metadata standard, a good starting place is the DataCite schema.

  • It has mandatory fields (e.g., creator, title of the dataset), and
  • recommended and optional fields that some funders might require (i.e., funding source and grant number), and other elements (e.g., subject, description, geolocation, format, version, rights information).


Because creation of standardized metadata can be difficult and time consuming, in some cases tools have been developed to help record metadata (e.g. Morpho allows for easy creation of Ecological Markup Language (EML) for ecological data; Nesstar for metadata for social science data).

If your discipline or repository does not require a specific metadata standard, or you would like assistance, contact us at