RDF (Resource Description Framework)

RDF structures all information as subject-predicate-object triples, forming a directed, labeled graph. The subject is the resource being described, the predicate defines the property or relationship, and the object is the value or target resource.

• Example: <http://example.org/Alice> <http://xmlns.com/foaf/0.1/knows> <http://example.org/Bob>
• Every triple is a single, unambiguous fact
• Triples can be combined to express complex, interconnected knowledge
• This atomic structure enables incremental data merging without schema conflicts

Every resource in RDF is identified by a Uniform Resource Identifier (URI) or a blank node for anonymous resources. This global naming convention eliminates ambiguity by ensuring that every entity, property, and class has a unique, dereferenceable identifier.

• URIs enable cross-dataset linking without name collisions
• Example: http://www.wikidata.org/entity/Q42 uniquely identifies Douglas Adams
• Blank nodes represent resources without explicit URIs, useful for complex structures
• This contrasts with relational databases, where identity is local to a table

RDF is an abstract data model independent of any specific file format. Multiple serialization syntaxes exist to represent RDF graphs for different use cases, each with distinct trade-offs in human readability and machine efficiency.

• Turtle (.ttl): Compact, human-readable syntax ideal for authoring
• JSON-LD: JSON-based format for embedding linked data in web pages
• RDF/XML: The original XML-based syntax, now largely legacy
• N-Triples: Line-based, minimal syntax for streaming and fast parsing
• N3 (Notation3): Superset of Turtle with logical rules and variables

RDF provides the data structure, while RDF Schema (RDFS) and the Web Ontology Language (OWL) provide the vocabulary to define classes, properties, and logical constraints. This layered architecture enables formal knowledge representation.

• RDFS defines class hierarchies (rdfs:subClassOf) and property domains/ranges
• OWL adds cardinality constraints, transitive properties, and equivalence assertions
• SHACL (Shapes Constraint Language) validates RDF graphs against structural rules
• Enables automated reasoning to infer new facts from explicit assertions

Beyond the basic triple, RDF supports quads by adding a fourth element: the graph name or context identifier. This enables grouping triples into sub-graphs for provenance tracking, access control, and dataset management.

• Each named graph is itself identified by a URI
• Enables tracking which source asserted a specific triple
• Critical for data provenance and trust assessment in federated queries
• Supported by SPARQL's GRAPH keyword for scoped querying
• Used in TriG and N-Quads serialization formats

SPARQL is the W3C-standard query language for RDF data, analogous to SQL for relational databases. It enables pattern matching across graph structures using graph patterns composed of triple templates with variables.

• SELECT queries return tabular results from matched patterns
• CONSTRUCT queries generate new RDF graphs from query results
• ASK queries return boolean true/false for pattern existence
• Federated queries (SERVICE keyword) span multiple remote SPARQL endpoints
• Supports property paths for traversing arbitrary-length graph connections