Valuecategory

Valuecategory is a term used in information science and data modeling to describe the semantic category of a data value. It specifies what kind of value a datum represents and what operations are meaningful for that value. The concept supports data validation, transformation, and interoperability across systems with heterogeneous type systems.

A typical valuecategory taxonomy includes numeric, string, boolean, date/time, null, and complex types such as array or object. Some schemas also recognize enumerated (or categorical) values and duration or interval types. The category is not the same as a data type in programming languages; instead, it provides a level of semantic interpretation used by validation rules and data integration pipelines.

The determination of a valuecategory can be explicit, via schema or metadata, or inferred from the literal value using rules (for example, digits-only strings may be treated as numeric if the context permits). In practice, valuecategory helps decide permissible operations: arithmetic on numeric values, concatenation on strings, temporal calculations on date/time values, and membership tests on enumerations.

In data workflows, valuecategory informs data cleansing, schema mapping, and API design, supporting robust handling when data moves between systems with different type representations. It is used in catalogs and metadata repositories to annotate fields with their expected value category.

See also: data type, data validation, schema, type system, interoperability.