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An example of a hierarchical metadata schema is the IEEE LOM schema, in which metadata elements may belong to a parent metadata element. Metadata schemata can also be one-dimensional, or linear, where each element is completely discrete from other elements and classified according to one dimension only.
A good example of metadata is the cataloging system found in libraries, which records for example the author, title, subject, and location on the shelf of a resource. Another is software system knowledge extraction of software objects such as data flows, control flows, call maps, architectures, business rules, business terms, and database schemas.
Metadata tags as described in this article should not be confused with the use of the word "tag" in some software to refer to an automatically generated cross-reference; examples of the latter are tags tables in Emacs [15] and smart tags in Microsoft Office. [16]
Business metadata is important because it can greatly facilitate the usefulness of the data to business people. A simple example of business metadata is a glossary entry. Hover functionality in an application or web form can enable a glossary definition to be shown when cursor is on a field or term.
A metadata repository is a database created to store metadata. Metadata is information about the structures that contain the actual data. Metadata is often said to be "data about data", but this is misleading. Data profiles are an example of actual "data about data".
Metadata management goes by the end-to-end process and governance framework for creating, controlling, enhancing, attributing, defining and managing a metadata schema, model or other structured aggregation system, either independently or within a repository and the associated supporting processes (often to enable the management of content).
Because metadata registries are used to store both semantics (the meaning of a data element) and systems-specific constraints (for example the maximum length of a string) it is important to identify what systems impose these constraints and to document them. For example the maximum length of a string should not change the meaning of a data element.
The ISO/IEC 11179 model is a result of two principles of semantic theory, combined with basic principles of data modelling. The first principle from semantic theory is the thesaurus type relation between wider and more narrow (or specific) concepts, e.g. the wide concept "income" has a relation to the more narrow concept "net income".