Metadata is often defined as "data about data". Metadata is used to describe and document research data. The good use of metadata makes it easier for researchers to 1) find data that is relevant to their research and 2) understand the data so it can be reused effectively.
There are three types of metadata; descriptive, structural, and administrative.
Descriptive metadata describes the data and its content to make it easier to find and identify.
Examples: title, creator, DOI, subjects, keywords
Structural metadata describes how the data is organized, such as folder structures or tables of contents.
Examples: Manifest of files in a dataset, table of contents, or schema of database tables
Administrative metadata helps in managing the resource by describing technical aspects, rights management, and preservation information.
Technical Examples: file type, version information, how/when created
Rights Management Examples: licensing, use restrictions, privacy concerns
Preservation Examples: ownership, history of use, authenticity
Whenever possible, data should be shared in reputable, established repositories. These repositories have their own metadata standards and forms you will be asked to fill out when sharing your data. It is rarely necessary for you to make up your own metadata fields or understand the underlying schema. Rather, focus on understanding the information needed for the repository you are using.
Many repositories have documentation or help files to assist you. If you are ever unsure of what a metadata field means, consult with a librarian.
The two most common metadata schemas used in data repositories are Dublin Core and Datacite. To better understand the meaning of metadata fields in most repositories, check out the links below.