SPARQL Fundamentals and Practical Querying Training Course

Introduction to RDF and SPARQL

• Foundations of RDF: triples, IRIs, literals, and blank nodes.
• Applying namespaces and QNames within queries.
• An overview of SPARQL query forms and their respective use cases.

Setting Up a SPARQL Environment

• Installing and running Apache Jena Fuseki or RDF4J Server.
• Loading sample RDF datasets into a triple store.
• Utilising a SPARQL client or workbench to execute queries.

Basic SPARQL SELECT Queries

• Writing triple patterns and retrieving bindings.
• Incorporating DISTINCT, LIMIT, and OFFSET.
• Sorting and projecting results using ORDER BY.

Filtering and Solution Modifiers

• Applying FILTER expressions and built-in functions.
• Using OPTIONAL for partial matching.
• Combining patterns with UNION and MINUS.

Advanced Querying: Aggregation and Subqueries

• Utilising GROUP BY, COUNT, SUM, MIN, MAX, and HAVING.
• Implementing nested queries and subselect patterns.
• Using expressions and bind() to compute values.

Constructing and Transforming RDF

• Using CONSTRUCT queries to build new RDF graphs.
• Exploring DESCRIBE and ASK query forms and their appropriate applications.
• Implementing SPARQL UPDATE for data modification (INSERT/DELETE).

Working with Graphs and Named Graphs

• Understanding quads and the GRAPH keyword.
• Managing and querying named graphs.
• Best practices for organising dataset graphs.

Federated Queries and Remote Endpoints

• Using SERVICE to query remote SPARQL endpoints.
• Performance considerations and timeout management.
• Strategies for combining local and remote data.

Practical Lab: Real-World SPARQL Tasks

• Querying DBpedia and other public datasets to gain insights.
• Building reusable query templates and views.
• Debugging common query errors and optimising performance.

Summary and Next Steps