Knowledge graphs are large networks of entities and their semantic relationships. They are a powerful tool that changes the way we do data integration, search, analytics, and context-sensitive recommendations. Knowledge graphs have been successfully utilized by the large Internet tech companies, with prominent examples such as the Google Knowledge Graph. Open knowledge graphs such as Wikidata make community-created knowledge freely accessible.

In this tutorial, we will cover the fundamentals of knowledge graphs and also present specific examples of application areas. We explain how organizations can create their own knowledge graphs and utilize them in novel applications.

In hands-on exercises we will create a small, but real knowledge graph, covering the entire lifecycle including integration and interlinking of existing sources, authoring, visualization, querying and search. The practical hands-on examples will be performed using the metaphactory Knowledge Graph Platform.


This tutorial will provide a comprehensive and in-depth introduction to knowledge graphs. We will start with an overview of knowledge graphs as they are used to today. The focus will be on open standards and technologies, in particular the W3C Semantic Web language stack. We will present specific examples and applications of knowledge graphs building on this stack (such as Wikidata), but also cover proprietary approaches like the Google Knowledge Graph.

We will then provide an overview of state-of-the-art approaches, concepts, techniques and tooling for creating knowledge graphs as well as building knowledge graph applications. Here, we will cover the entire lifecycle, including:
  • Creating and interlinking knowledge graphs from existing data
  • End-user authoring of knowledge graphs
  • Visualization and exploration of knowledge graphs
  • Semantic search over rich knowledge graphs
Overall, the tutorial will maintain a balance between theoretical foundations, examples of applications (in-use) and own hands-on experience. For the practical exercises, we will use the metaphactory Knowledge Graph Platform, which will be provided to all participants. The participants will import a sample knowledge graph, augment it and author their own data, write queries, create visualizations and customize interfaces for interacting with the knowledge graph.

The tutorial aims at both novices who want to understand basic concepts and value adds delivered by knowledge graphs, as well as practitioners who want to get started with knowledge graphs - both in academia as well as industry.

The tutorial should also be interesting for educators (such as lecturers and professors) who want to introduce practical exercises into their own lectures: All material provided in the tutorial will be made freely available (open source software; slides and exercises under Creative Commons Share Alike) in reusable form.

At the same time, the tutorial software and exercises will not only provide a playground, but offer a clear path for practitioners considering to introduce knowledge graphs into their industrial applications: The metaphactory is a commercial platform backed by a company with commercial offerings.