NonRDF

NonRDF is a term used to describe data, schemas, or information systems that do not adopt the Resource Description Framework (RDF) triple-based model as their primary means of expressing meaning. In practice, nonRDF coverage includes data stored in CSV, relational databases, XML, and many JSON structures that do not rely on RDF triples.

RDF encodes information as subject-predicate-object triples, usually identified by URIs. RDF data are serialized in formats such as Turtle, RDF/XML, N-Triples, or JSON-LD, to support graph-based querying and linking. NonRDF representations use different schemas or encodings and do not guarantee the same explicit graph semantics.

Usage and implications: In domains with established relational databases, document stores, or web APIs designed without RDF, nonRDF data are common. Projects that require RDF semantics may introduce adapters, ETL processes, or mappings to translate nonRDF sources into RDF graphs, or to expose parallel RDF interfaces.

Limitations and considerations: NonRDF data can complicate data integration, provenance, and semantic interoperability due to the lack of a single universal standard for meaning. However, nonRDF formats may offer performance, simplicity, and compatibility with existing tooling in many applications.

See also: RDF, Linked Data, JSON-LD, data interoperability.