Metadata is commonly defined as 'data about data.' But I like to think of metadata as telling a 'story about data' that gives life to an otherwise dry subject; stories that tell where the data comes from, how old it is, who made it, when it was last updated, and so on.

Its also a story that can give meaning and intelligence to machines through controlled dictionaries, vocabularies, glossaries, thesauri, hierarchies, taxonomies, ontologies, and knowledge graphs.

Operational metadata

Profiles data or data content for determining what the data can be used for. Powers the data lifecycle process for assessing where to store and how long to keep the data (hot, warm, cold).

Used for Identification (terms, languages, author, subject, keyword, title, publisher, type, definition), Quality, Validation, Reliability, Lineage (provenance), and Metrics (freshness, duplicates)

Structural metadata

Data about the containers of data; order/organization information, like page order, tables, columns, keys, indexes, and relationships.

Administrative metadata

Information describing Rights Management (intellectual property, ownership, source, access, digital rights, privacy) and Preservation (created date, file type, file version, and retention)

Business process metadata

Models and rules.