Ontology-mediated query answering over temporal and inconsistent data

Tracking #: 1920-3133

This paper is currently under review
Camille Bourgaux
Patrick Koopmann
Anni-Yasmin Turhan

Responsible editor: 
Guest Editors Stream Reasoning 2017

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Full Paper
Stream-based reasoning systems process data stemming from different sources and that are received over time. In this kind of applications, reasoning needs to cope with the temporal dimension and should be resilient against inconsistencies in the data. Motivated by such settings, this paper addresses the problem of handling inconsistent data in a temporal version of ontology-mediated query answering. We consider a recently proposed temporal query language that combines conjunctive queries with operators of propositional linear temporal logic, and consider these under three inconsistency-tolerant semantics that have been introduced for querying inconsistent description logic knowledge bases. We investigate their complexity for EL_bot and DL-Lite_R temporal knowledge bases. In particular, we consider two different cases, depending on the presence of negations in the query. Furthermore, we complete the complexity picture for the consistent case. We also provide two approaches toward practical algorithms for inconsistency-tolerant temporal query answering.
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