Data is usually not self-explanatory and therefore needs additional information, the so-called metadata. Metadata is structured information (data) about other data and their characteristics and is therefore essential for finding, understanding and re-using research data. By establishing standards for different values and fields, data sets can be related to each other, made readable and processable by machines, and made discoverable and understandable across institutional, linguistic and disciplinary boundaries.

There are different types of metadata with different functions.

  • Bibliographic metadata such as title, authors, description or keywords enable the citation of data and code and help with findability and thematic delimitation.

  • Administrative metadata on file types, locations, access rights and licences help with the management and long-term preservation of data.

  • Process metadata describes the steps and actions with their methods and tools used to create and process the data.

  • Content descriptive metadata can be structured very differently depending on the discipline and provide additional information on the content and origins of the data.

Bibliographic and administrative metadata can be standardised across disciplines. Process metadata and content descriptive metadata of research results often have a very discipline-specific structure and content. But it is precisely this subject-specific information that is often crucial for the discoverability and traceability of research data. Therefore, there are many different metadata standards that provide a structure for the relevant information in a field or discipline.

Overview of existing standards: