modelDescription

modelDescription is a term used in information systems to denote metadata that describes a model. It can be a label, field, or structured object that summarizes the model’s purpose, scope, inputs, outputs, and other relevant attributes. In practice, modelDescription appears in model catalogs, APIs, data dictionaries, and model-driven engineering artifacts to aid discovery, governance, and reuse. It distinguishes the model from the data, code, and artifacts that implement it.

Typical contents include: intended use, domain, target variable, input schema, data preprocessing steps, assumptions and constraints, model type or algorithm, key parameters, training data characteristics, performance metrics, validation results, limitations, caveats, provenance such as authors and version, licensing, and maintenance status. It may also note ethical, legal, or bias considerations and any retraining or versioning requirements.

Model descriptions may be free text or structured in JSON, YAML, or RDF, and can align with metadata standards such as schema.org, Dublin Core, or domain-specific ontologies. In API or service ecosystems, a field named modelDescription may be part of a model manifest or registry entry.

Uses include model discovery, comparison, auditing, and compliance. A well-maintained description supports reproducibility, explainability, and responsible deployment by making assumptions explicit and guiding future maintenance.

Best practices include keeping the description concise yet comprehensive, versioning the description along with the model, updating it after retraining or changes in inputs, and avoiding sensitive content. Related concepts are model cards, provenance and lineage, metadata catalogs, and model registries.