Graph Computing Training in Gaia

SPARQL is the W3C-standard query language used to retrieve and manipulate RDF data from triple stores and SPARQL endpoints.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level participants who wish to learn practical SPARQL querying for data retrieval, transformation, and federation.

Upon completion of this training, participants will be able to:

• Construct basic and advanced SPARQL SELECT queries to retrieve RDF data.
• Use FILTER, OPTIONAL, and UNION to refine query results.
• Write CONSTRUCT and DESCRIBE queries to transform RDF graphs.
• Query remote endpoints and perform federated queries using SERVICE.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises against live SPARQL endpoints.
• Guided labs with sample RDF datasets and troubleshooting.

Course Customization Options

• To request a customized version focusing on your organisation’s data model or specific SPARQL endpoints, please contact us to arrange.

This instructor-led, live training in Gaia (online or onsite) is designed for technical professionals seeking to query RDF data stored in Semantic Web databases.

By the end of this training, participants will be able to:

• Understand the difference between semantic web data and relational data.
• Query public datasets based on Semantic Web standards.
• Model data for querying with SPARQL.
• Transition a website's data to semantic web linked data.
• Run SPARQL queries from within an existing application.

Clarifies the extensive capabilities of Semantic MediaWiki—ranging from structured semantic searches and knowledge graph queries to intelligent content navigation, along with sophisticated editing workflows integrated with the Semantic Web. The course covers fundamental methods for connecting data, establishing metadata-driven content frameworks, and developing smart collaboration environments that enable teams to automate cataloging, reveal underlying links, and revolutionize how organizations discover, manage, and distribute knowledge at scale across various domains.