Matricat

Matricat is a term used in theoretical discussions and experimental software projects to denote a data construct that combines a numeric matrix with an associated metadata layer. The term is not tied to a single, widely adopted standard; it has appeared in informal contexts as a shorthand for matrix-centric cataloging and contextual data management.

Conceptually, a matricat consists of two components: a two-dimensional array of numbers and a metadata layer that can store attributes such as names, units, provenance, and annotations. The metadata can be attached at various granularity levels (elements, rows, columns, or the entire matrix) and is intended to accompany matrix operations to preserve context during transformations.

Key features discussed in literature include support for metadata propagation through arithmetic and linear algebra operations, serialization to common formats (such as CSV with separate metadata, JSON, or HDF5), and interoperability with data catalogs. Some discussions emphasize provenance tracking and reproducibility in scientific workflows, where maintaining metadata alongside data is important.

Applications cited for matricat concepts include research data management, educational tools for teaching linear algebra with descriptive context, and experimental software libraries that prototype matrix-centric data models. Because matricat lacks a formal standard, implementations vary in data model, API, and compatibility with existing matrix and data-catalog ecosystems.

See also: Matrix, Metadata, Data provenance, Data catalog, Linear algebra.