Ontology-based query answering (OBQA) augments classical query answering in databases by domain knowledge encoded in an ontology. Systems for OBQA use the ontological knowledge to infer new information that is not explicitly given in the data. Moreover, they usually employ the open-world assumption, which means that knowledge that is not stated explicitly in the data and that is not inferred is not assumed to be true or false. Classical OBQA however considers only a snapshot of the data, which means that information about the temporal evolution of the data is not used for reasoning and hence lost. We investigate temporal conjunctive queries (TCQs) that allow to access temporal data through classical ontologies. In particular, we study combined and data complexity of TCQ entailment for ontologies written in description logics from the extended DL-Lite family. Many of these logics allow for efficient reasoning in the atemporal setting and are successfully applied in practice. We show comprehensive complexity results for temporal reasoning with these logics.

中文翻译：

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扩展 DL-Lite 系列中的时间连接查询应答

基于本体的查询应答 (OBQA) 通过本体编码的领域知识增强了数据库中的经典查询应答。OBQA 系统使用本体知识来推断数据中未明确给出的新信息。此外，它们通常采用开放世界假设，这意味着数据中未明确说明且未推断的知识不会被假定为真或假。然而，经典的 OBQA 只考虑数据的快照，这意味着有关数据时间演变的信息不会用于推理，因此会丢失。我们研究了允许通过经典本体访问时间数据的时间连接查询 (TCQ)。特别是，我们研究了用扩展 DL-Lite 系列的描述逻辑编写的本体的 TCQ 蕴涵的组合和数据复杂性。许多这些逻辑允许在非时间环境中进行有效推理，并在实践中成功应用。我们展示了使用这些逻辑进行时间推理的综合复杂性结果。