This course provides a practical introduction to Linked Data technologies and their applications, equipping learners with the knowledge and tools of the Semantic Web. Focusing on real-world use cases, this course combines theory and practice to help participants explore the potential of Dynamic Linked Data.
Purpose
As a first step, the course aims to provide learners with a solid foundation in Semantic Web technologies. By the end of the course, learners will not only understand how to structure, publish, and query semantic datasets but also implement Dynamic Linked Data applications, which combine real-time data capabilities with interoperability for building data-driven systems.
Target
This course is ideal for software developers, researchers, academics, and technology enthusiasts seeking to apply Semantic Web standards to real-world scenarios.
Key knowledge and skills
Participants will gain a complete understanding of Semantic Web technologies. They will develop expertise in querying and publishing Linked Data, along with hands-on experience in implementing Dynamic Linked Data. Additionally, learners will acquire the skills needed to design and build interoperable, data-driven applications.
Course structure
- Introduction: overview of Linked Data principles.
- Fundamental technologies: RDF, RDFS, OWL, TTL, JSON-LD, SPARQL 1.1, RDF-star, SPARQL-star.
- Tools: Protegè, Drools, JENA, Blazegraph, Virtuoso, Neptune, Stardog.
- Well-known ontologies: SOSA, QUDT, TIME, AGROVOC.
- Dynamic Linked Data applications: SEPA (SPARQL Event Processing Architecture).
- Use case: Agorà – The Agritech Oracle.
Format and practical information
- Duration: 50 hours Delivery format: online.
- Assessment: practical exercises and project-based evaluation.
- Prerequisites: Java, Javascript are required.
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