What is RDF?

RDF (Resource Description Framework) is the W3C standard for representing data as subject-predicate-object triples: every statement ("this supplier supplies this component") becomes an elementary unit made of three parts, instead of a row in a table linked to others through foreign keys. Subject and predicate are identified by an IRI, the internationalized evolution of the URI, and so is the object whenever it points to another resource (it can also be a literal value, such as a number or a string, when the triple terminates a piece of data instead of linking it elsewhere). Using global unique identifiers instead of local keys has a precise consequence: two different organizations can refer to the same entity with the same IRI and link their data without semantic ambiguity, the principle behind linked data. The model started as a W3C recommendation in 1999, was rewritten in a sturdier form in 2004, and was further refined with RDF 1.1 in 2014.

Triples, serializations and the difference from a property graph

An RDF triple is written in several concrete formats, all interchangeable because they represent the same abstract graph: Turtle is the most human-readable (:supplierA :supplies :componentX .), JSON-LD wraps the same graph inside ordinary JSON and is the format most used to publish structured data on the web, N-Triples is the more verbose form, simplest to process line by line. This sets RDF apart from a generic property graph, where nodes and edges carry arbitrary key-value properties decided case by case by whoever designs the schema: RDF is a stricter, standardized model, built specifically for interoperability across different systems and organizations, not just for a single application's database. Querying an RDF graph is done with SPARQL, the standard language dedicated to this model. When formal semantics with verifiable inference rules are also needed, the layer above RDF is OWL, which uses the same triple model as its foundation.

An enterprise example: linked data across organizations

The use case that justifies RDF over a simpler proprietary model is integrating data across organizations that do not share the same internal schema. The BBC built its Dynamic Semantic Publishing platform on an RDF triple store queried via SPARQL to run the 2010 World Cup website and its ongoing news and sport metadata, precisely because the global identifier (the IRI) lets different newsrooms and systems recognize "this is the same entity" without first agreeing on a point-to-point mapping with one another. It is the same principle that makes an enterprise knowledge graph reusable beyond a single team's boundaries when its internal representation is built on RDF.

Why it matters for decision makers

Adopting RDF has a real cost: it requires explicitly modeling the domain with IRIs and shared vocabularies, an effort a simple application-level property graph does not demand. It is worth it when the benefit of interoperability (data linkable across different systems with no rewrites, an open standard tied to no single vendor) outweighs the cost of that extra discipline. For a graph internal to a single product, with no need to exchange data externally, a simpler property graph often remains the more economical choice.