Semantic Web Research

Photo: Karl Öfverström

The Semantic Web is an extension of the traditional Web in which interlinked data with well-described semantics has been added in a machine-processable form. As a result, we can view the whole Web as a large set of interconnected knowledge bases that can be queried and browsed both by software systems and by human users.

Research into the Semantic Web at LiU includes areas such as:

  • Ontologies and ontology engineering (ontology design patterns, ontology alignment and completion, ontology and alignment visualization).
  • Graph databases and triple stores.
  • Querying interlinked data on the web.
  • RDF stream processing
  • Complex event processing.
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Our group

We are researchers from different labs in the Department of Computer and Information Science (IDA) at LiU, with a common interest in the Semantic Web.

Research leaders

Junior researchers

Doctoral students

Publication list

2026

Huanyu Li, Els de Vleeschauwer, Robin Keskisärkkä, Mikael Lindecrantz, Mina Abd Nikooie Pour, Ying Li, Ben De Meester, Patrick Lambrix, Eva Blomqvist (2026) CEON: Circular Economy Ontology Network The Semantic Web – ISWC 2026: 25th International Semantic Web Conference, Bari, Italy, October 25–29, 2026, Proceedings, Part II (Conference paper)
Mohammad Javad Saeedizade, Reham Alharbi, Hamed Babaei Giglou, Anna Sofia Lippolis, Eva Blomqvist, Valentina Tamma, Floriana Grasso, Terry R. Payne, Jennifer D'Souza, Soren Auer, Andrea Giovanni Nuzzolese, Robin Keskisärkkä, Zebah Valeyil (2026) A Framework for Assessing LLM Consistency in Knowledge Engineering Semantic Web, Vol. 17, Article 22104968261479512 (Article in journal) https://dx.doi.org/10.1177/22104968261479512
Tim Brecht, Niklas Carlsson, Adam Almqvist Richloow, Mikael Vernblom, Patrick Lambrix (Editorship) (2026) Proceedings of the 5th International Ice Hockey Analytics Conference LINHAC 2026 Research Track and Community Notes (Conference proceedings (editor)) https://dx.doi.org/10.3384/ecp221
Riley Capshaw (2026) Composing Meaning from Text: Improving Entity Representations for Ontology-based Document Modeling using Masked Language Models (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789181186321

Semantic Web Research Archive

News

Divisions

Department