Knowledge graphs are becoming an important paradigm in industry and research, with applications including prominent examples such as Google's own Knowledge Graph, Wikipedia's knowledge base sister Wikidata, and numerous artificial intelligence projects from Alexa to Siri. Meanwhile, companies are exploring the use of their own enterprise knowledge graphs for improving internal knowledge management.
With so many facets, knowledge graphs are a cross-cutting topic in computer science that involves aspects of data management (graph databases, file formats), publication (exchange formats, data integration), knowledge organisation (constraints, ontologies), and advanced analytics (expressive query languages, graph data mining). On each of these levels, there is some interesting theory and some interesting technology to be learned. This course will cover a colourful mix of technologies and methods related to the use of graphs for data analysis, knowledge representation, and data management.