Ontology mappings

Connect RDF vocabulary to property-graph labels, identities, properties, and relationship directions.

Class mappings

OntologyMapping::class(iri, label) associates a class IRI with a graph label:

let ontology = OntologyMapping::new()
    .class("https://example.com/Person", "Person");

A pattern such as ?p a ex:Person then selects nodes with the Person label.

Subject identity

Use class_with_identity when a graph property provides the externally visible subject:

let ontology = OntologyMapping::new()
    .class_with_identity("https://example.com/Person", "Person", "iri");

Map that graph property to your physical identity column in the graph mapping:

mapping.map_node(
    NodeMapping::table("Person", "people", "id")
        .property("iri", "person_iri")
        .property("name", "full_name")
);

The relational ID identifies the node for graph joins; the identity property supplies the vocabulary-facing subject.

Property predicates

property(iri, domain_label, property) maps a predicate to a graph property:

let ontology = OntologyMapping::new()
    .class("https://example.com/Person", "Person")
    .property("https://example.com/name", "Person", "name")
    .property("https://example.com/age", "Person", "age");

The graph mapping resolves name and age to physical columns. This keeps the RDF vocabulary independent of database column names.

Relationship predicates

Use relationship_between to make both endpoint labels explicit:

use orchiddb::ir::plan::Direction;

let ontology = OntologyMapping::new()
    .class("https://example.com/Person", "Person")
    .class("https://example.com/Order", "Order")
    .relationship_between(
        "https://example.com/ordered", "ORDERED", Direction::Out,
        "Person", "Order",
    );

The direction defines how a subject-to-object triple follows the graph relationship. Use Direction::In for a vocabulary predicate that follows the inverse graph direction.

relationship(iri, rel_type, direction) configures the predicate without explicit endpoint labels. Use the endpoint-aware builder when those labels are known in your vocabulary.

Reuse one vocabulary

Pass the same ontology to managed or mapped graph SPARQL methods. This allows application queries to share vocabulary while the graph mapping determines physical storage.

Shared RDF catalog

For mapped storage, GraphEngine::sparql(query, ontology) translates ontology builders into the same relational RDF rules used by GraphMapping::map_rdf. To install those rules in a named dataset before engine construction, call ontology.apply_to(&mut mapping, "default")?, then use sparql_query or sparql_dataset. Query patterns need not start with an explicit type assertion. An ontology is optional when rules already map RDF terms directly to columns. See RDF mappings for composite identities and writable row rules.