Abstract
The paper contributes to the recent efforts on temporalizing and streamifiying ontology based data access (OBDA) by discussing aspects of rewritability, i.e., compilability of the TBox into ontology-level queries, and unfoldability, i.e., transformability of ontology-level queries to queries on datasource level, for the new query-language framework STARQL. The distinguishing feature of STARQL is its general stream windowing and ABox sequencing strategy which allows it to plugin well-known query languages such as unions of conjunctive queries (UCQs) in combination with TBox languages such as DL-Lite and do temporal reasoning with a sorted first-order logic on top of them. The paper discusses safety aspects under which STARQL queries that embed UCQs over DL-Lite ontologies can be rewritten and unfolded to back-end relational stream query languages such as CQL. With these results, the adoption of description logic technology in industrially relevant application areas such as industrial monitoring is crucially fostered.
This work has been supported by the European Commission as part of the FP7 project Optique.
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Özçep, Ö.L., Möller, R., Neuenstadt, C. (2014). A Stream-Temporal Query Language for Ontology Based Data Access. In: Lutz, C., Thielscher, M. (eds) KI 2014: Advances in Artificial Intelligence. KI 2014. Lecture Notes in Computer Science(), vol 8736. Springer, Cham. https://doi.org/10.1007/978-3-319-11206-0_18
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DOI: https://doi.org/10.1007/978-3-319-11206-0_18
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