Christoph Schuetz, Institute of Business Informatics – Data & Knowledge Engineering, Johannes Kepler Universität Linz
The Role of Knowledge Graphs in (Big) Data Analytics: Past, Present, and Future
Abstract A knowledge graph represents real-world entities and their relationships with each other in a machine-readable format. Knowledge graphs comprise both terminological/ontological knowledge (vocabulary and schema information) and assertional knowledge (instance data). Even though originating in a different context, researchers and practitioners have discovered the usefulness of knowledge graphs for business intelligence and analytics. In this context, among the first uses of knowledge graphs was the representation of metadata for analytics applications, with knowledge graphs serving as a facilitator for conducting various analytical tasks and for correctly interpreting the results. Meanwhile, knowledge graphs have themselves become a prime data source for analytics. In this regard, the management and analysis of big knowledge graphs poses a considerable challenge, which requires the development of analytics infrastructures that are up to the task. This talk will explore the evolving role of knowledge graphs in business intelligence and analytics, and discuss possible future research directions and challenges, especially with regard to the management and analysis of big knowledge graphs.
Short Bio: Christoph Schuetz is associate professor at Johannes Kepler University (JKU) Linz, Austria. He received his doctorate degree from JKU in 2015. In 2014, he was a visiting researcher on a Marietta Blau Grant at the University of Konstanz, Germany. In 2012, he was a visiting researcher on a Marshall Plan Scholarship at Portland State University, Oregon, USA. Christoph was work package leader and key researcher in multiple collaborative research projects with industry partners, funded by the European Union and national research programs. His main research interests are knowledge graphs, business intelligence, and business analytics.