Tutorial : Shaping Linked Data and Knowledge Graphs

Linked data and knowledge graphs provide an interconnected way to represent complex information, enabling smarter data integration, querying and discovery. In this tutorial we will overview some of the data models proposed for Knowledge graphs: RDF in the context of the Semantic Web, Property Graphs in graph databases, and Wikibase which is proposed in the context of Wikidata. We will also present the recent proposal of RDF-1.2, which could bridge the gap between those data models by allowing statements about statements. The quality of data within these graphs is more and more important, often checked with expected data models or shapes. We will present some approaches that have been developed to describe and validate RDF like Shape Expressions (ShEx) or Shapes Constraint Language (SHACL). We will briefly describe them and show some differences. Our aim is to present the different types of Knowledge Graphs and the approaches for their validation using examples and tools that showcase how those technologies can be used in practice. Time permiting, we will also review some practical applications of these technologies like inferring shapes from existing data or generating conforming subsets of Knowledge Graphs.