This module looks in great detail at SPARQL and introduces approaches for querying and updating semantic data. It covers the SPARQL algebra, the SPARQL 1.1 protocol, and provides examples for reasoning over Linked Data. The module uses examples from the music domain, which can be directly tried out and ran over the MusicBrainz dataset. This includes gaining familiarity with the RDFS and OWL languages, which allow developers to formulate generic and conceptual knowledge that can be exploited by automatic reasoning services in order to enhance the power of querying.
Keywords: Inferencing, SPARQL, RDF Schema, Web Ontology Language (OWL), Semantic Web, Entailment
Author: Norton, Barry
Publisher: EUCLID Project
Time required: P3H
Educational use: professionalDevelopment
Educational audience: professional
Interactivity type: expositive
- Demonstrates a working knowledge of the forms and uses of SPARQL result sets (SELECT, CONSTRUCT, DESCRIBE, and ASK).
- Understands how to combine and filter graph patterns using operators such as UNION, OPTIONAL, FILTER, and MINUS.
- Understands that a SPARQL query matches an RDF graph against a pattern of triples with fixed and variable values.
- Knows that Web Ontology Language (OWL) is available in multiple "flavors" that are variously optimized for expressivity, performant reasoning, or for applications involving databases or business rules
- Understands the principles and practice of inferencing.
- Knows the SPARQL 1.1 Update language for updating, creating, and removing RDF graphs in a Graph Store
- Understands the difference between SQL query language (which operates on database tables) and SPARQL (which operates on RDF graphs).
- Uses common entailment regimes and understands their uses.