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Ontology-based query answering (OBQA) augments classical query answering indatabases by domain knowledge encoded in an ontology. Systems for OBQA use theontological knowledge to infer new information that is not explicitly given inthe data. Moreover, they usually employ the open-world assumption, which meansthat knowledge that is not stated explicitly in the data and that is notinferred is not assumed to be true or false. Classical OBQA however considersonly a snapshot of the data, which means that information about the temporalevolution of the data is not used for reasoning and hence lost. We investigatetemporal conjunctive queries (TCQs) that allow to access temporal data throughclassical ontologies. In particular, we study combined and data complexity ofTCQ entailment for ontologies written in description logics from the extendedDL-Lite family. Many of these logics allow for efficient reasoning in theatemporal setting and are successfully applied in practice. We showcomprehensive complexity results for temporal reasoning with these logics.

Temporal Conjunctive Query Answering in the Extended DL-Lite Family