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Stream-Query Compilation with Ontologies

Part of the Lecture Notes in Computer Science book series (LNAI,volume 9457)

Abstract

Rational agents perceiving data from a dynamic environment and acting in it have to be equipped with capabilities such as decision making, planning etc. We assume that these capabilities are based on query answering with respect to (high-level) streams of symbolic descriptions, which are grounded in (low-level) data streams. Queries need to be answered w.r.t. an ontology. The central idea is to compile ontology-based stream queries (continuous or historical) to relational data processing technology, for which efficient implementations are available. We motivate our query language STARQL (Streaming and Temporal ontology Access with a Reasoning-Based Query Language) with a sensor data processing scenario, and compare the approach realized in the STARQL framework with related approaches regarding expressivity.

Keywords

  • Stream
  • Rewriting
  • Ontology
  • Description logic

This work has been supported by the European Commission as part of the FP7 project Optique.

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Fig. 1.

Notes

  1. 1.

    For a longer version of this paper see: https://dl.dropboxusercontent.com/u/65078815/AI15Stream.pdf.

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Correspondence to Özgür Lütfü Özçep .

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Özçep, Ö.L., Möller, R., Neuenstadt, C. (2015). Stream-Query Compilation with Ontologies. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_40

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_40

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