An OWL Ontology for Biographical Knowledge. Representing Time-Dependent Factual Knowledge

Hans-Ulrich Krieger; Thierry Declerck

In: Proceedings of the First Conference on Biographical Data in a Digital World 2015. Biographical Data in a Digital World (BD-2015), April 9, Amsterdam, Netherlands,, 7/2015.


Representing time-dependent information has become increasingly important for reasoning and querying services defined on top of RDF and OWL. In particular, addressing this task properly is vital for practical applications such as modern biographical information systems, but also for the Semantic Web/Web 2.0/Social Web in general. Extending binary relation instances with temporal information often translates into a massive proliferation of useless container objects when trying to keep the underlying RDF model. In this paper, we argue for directly extending RDF triples with further arguments in order to easily represent time-dependent factual knowledge and to allow for practical forms of reasoning. We also report on a freely available lightweight OWL ontology for representing biographical knowledge that models entities of interest via a tri-partite structure of the pairwise disjoint classes Abstract, Object, and Happening. Even though the ontology was manually developed utilizing the Protege ontology editor, and thus sticking to the triple model of RDF, the meta-modelling facilities allowed us to cross-classify all properties as being either synchronic or diachronic. When viewing the temporal arguments as "extra" arguments that only apply to relation instances, universal biographical knowledge from the ontology can still be described as if there is no time.


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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence