Introduction to knowledge graphs
  • Concepts relevant for understanding knowledge graphs and introduction to relevant languages and standards:
    • RDF as underlying graph data model
    • RDFS and OWL as ontology and knowledge representation languages
    • SPARQL (with relevant extensions) as query language for querying knowledge graphs
    • SKOS as knowledge organization scheme to capture thesauri and terminologies
Applications of knowledge graphs
  • Use cases in knowledge management, data integration, data publishing, smart data access and analytics
  • Specific applications in various verticals: business, industry and cultural heritage
  • Community-driven knowledge graphs, such as Wikidata
Creating and interlinking knowledge graphs from existing data
  • Transformation and integration of legacy sources
  • Interlinking across sources, enrichment of data
End-user authoring of knowledge graphs
  • Interfaces and tooling for creating knowledge graphs
  • End-user oriented knowledge capturing
Visualization and exploration of knowledge graphs
  • Overview of various paradigms for visualization, using charts, graphs, diagrams, etc.
  • Creation of domain-specific visualizations
  • Tools for interactive exploration
Semantic search over rich knowledge graphs
  • Concepts, techniques and tooling to enable end users to express rich information needs
  • Query formulation, refinement, multi-modal result visualization and exploration