Abstract:
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.