The Role of Knowledge Graphs in (Big) Data Analytics: Past, Present, and Future (Online presentation)

Description

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. Keywords: Knowledge Graph, Ontologies, Knowledge Representation, Business Intelligence, Business Analytics, Big Data

Period	05 Sept 2022
Event title	K-GALS 2022 - Workshop on Knowledge Graph Analysis on a Large Scale (K-GALS), collocated with the 26th European Conference on Advances in Databases and Information Systems (ADBIS 2022), Turin, Italy
Event type	Conference
Location	ItalyShow on map