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Duration 4 hours
Course Outline
Introduction to RDF and SPARQL
- Foundations of RDF: triples, IRIs, literals, and blank nodes
- Utilizing Namespaces and QName within queries
- Overview of SPARQL query forms and their applicable use cases
Setting Up a SPARQL Environment
- Installation and execution of Apache Jena Fuseki or RDF4J Server
- Loading sample RDF datasets into a triple store
- Running queries using a SPARQL client or workbench
Basic SPARQL SELECT Queries
- Creating triple patterns and retrieving result bindings
- Applying DISTINCT, LIMIT, and OFFSET clauses
- Sorting and projecting results through ORDER BY
Filtering and Solution Modifiers
- Implementing FILTER expressions and built-in functions
- Using OPTIONAL for partial matching scenarios
- Combining patterns with UNION and MINUS
Advanced Querying: Aggregation and Subqueries
- Using GROUP BY, COUNT, SUM, MIN, MAX, and HAVING
- Constructing nested queries and subselect patterns
- Computing values with expressions and the bind() function
Constructing and Transforming RDF
- Using CONSTRUCT queries to generate new RDF graphs
- Understanding DESCRIBE and ASK query forms and their appropriate contexts
- Modifying data with SPARQL UPDATE (INSERT/DELETE)
Working with Graphs and Named Graphs
- Understanding Quads and the GRAPH keyword
- Managing and querying named graphs
- Best practices for organizing dataset graphs
Federated Queries and Remote Endpoints
- Querying remote SPARQL endpoints using SERVICE
- Addressing performance considerations and timeout management
- Strategies for integrating local and remote data sources
Practical Lab: Real-World SPARQL Tasks
- Extracting insights by querying DBpedia and other public datasets
- Developing reusable query templates and views
- Debugging common query errors and optimizing performance
Summary and Next Steps
Requirements
- A solid understanding of the RDF data model and triple structure.
- Familiarity with fundamental HTTP and JSON concepts.
- Proficiency in reading and writing basic programming logic or query expressions.
Target Audience
- Data engineers and integrators.
- Semantic web developers.
- Analysts working with linked data.
Testimonials (1)
Very nice training
