
Writing a data management plan: metadata - data about data
What does metadata mean?
The term metadata is commonly defined as "data about data." The difference between documentation and metadata is that the first is meant to be read by humans and the second implies computer-processing (though may also be human-readable). Documentation is sometimes considered a form of metadata, because it is information about data, but the importance of metadata lies in the potential for machine-to-machine interoperability, providing the user with an enhanced version of published data.
Three broad categories of metadata are:
- Descriptive - common fields such as title, author, abstract, keywords which help users to discover online sources through searching and browsing.
- Administrative - preservation, rights management, and technical metadata about formats.
- Structural - how different components of a set of associated data relate to one another, such as a schema describing relations between tables in a database.
Metadata may not be required if you are working alone on your own computer, but become crucial when data are shared online. Your data management plan should determine whether you need to apply metadata descriptors or tags at some point during your project.
Metadata help to place your dataset in a broader context, allowing those outside your institution, discipline, or software environment to understand how to interpret your data.