representationdescribing

Representationdescribing is a term used to denote the practice of articulating the properties, structure, and semantics of representations employed within a system or theory. It is not a fixed formal field, but a cross-disciplinary activity that appears in mathematics, computer science, cognitive science, linguistics, and information systems. The central aim is to describe how entities are encoded, transformed, and interpreted, rather than to generate the representations themselves.

In mathematics and theoretical computer science, representationdescribing involves detailing representations of algebraic structures, such as group representations or vector space representations, including the domain and codomain, the defining maps, basis choices, and invariants like characters. In cognitive science and AI, it concerns describing internal or learned representations—what features or latent dimensions are used, how they relate to inputs, and how they support inference. In data engineering and knowledge management, it includes describing data encodings, schemas, ontologies, and metadata that explain how information is stored, transmitted, and reasoned about.

Methodologically, representationdescribing draws on formal specification languages, schemas, ontologies, documentation practices, and visualization. It emphasizes traceability, interoperability, and explainability, providing precise descriptions that can be checked, validated, or compared across systems. Challenges include aligning descriptions across domains, managing varying levels of abstraction, and maintaining up-to-date documentation as representations evolve.

See also: representation theory, data modeling, ontologies, description logics.