The increasing amount and heterogeneity of data in distributed environments, such as the Web, poses challenges with respect to searching, using and understanding data. The research group Data & Knowledge Engineering (DKE) conducts research at the intersection of semantic technologies, information retrieval and natural language processing, aimed at understanding and searching heterogeneous data, information and knowledge on the Web. In particular, we develop methods and tools for retrieval, extraction and verification of entity-centric knowledge, facts or claims, for linking and semantic enrichment of large corpora, such as Web crawls or bibliographic archives) or, to automatically understand, classify and support user’s search and navigation behavior.
While the DKE chair also is scientific director of the department “Knowledge Technologies for the Social Sciences” at “GESIS – Leibniz Institute for the Social Sciences”, our research group applies research results as part of innovative data-driven infrastructures for the social sciences. In that context, a particular focus is on reproducible and transparent methods for analysing big data within the social sciences, for instance, aimed at opinion mining from social media to understand evolving attitudes and opinions or effects of misinformation on the Web.