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Ontology Based Data Access on Temporal and Streaming Data

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 8714)

Abstract

Though processing time-dependent data has been investigated for a long time, the research on temporal and especially stream reasoning over linked open data and ontologies is reaching its high point these days. In this tutorial, we give an overview of state-of-the art query languages and engines for temporal and stream reasoning. On a more detailed level, we discuss the new language STARQL (Reasoning-based Query Language for Streaming and Temporal ontology Access). STARQL is designed as an expressive and flexible stream query framework that offers the possibility to embed different (temporal) description logics as filter query languages over ontologies, and hence it can be used within the OBDA paradigm (Ontology Based Data Access in the classical sense) and within the ABDEO paradigm (Accessing Big Data over Expressive Ontologies).

Keywords

  • Ontology Based Data Access
  • streams
  • temporal logics
  • rewriting
  • unfolding
  • semantic web

This work has been supported by the European Commission as part of the FP7 project Optique http://www.optique-project.eu/

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Özçep, Ö.L., Möller, R. (2014). Ontology Based Data Access on Temporal and Streaming Data. In: , et al. Reasoning Web. Reasoning on the Web in the Big Data Era. Reasoning Web 2014. Lecture Notes in Computer Science, vol 8714. Springer, Cham. https://doi.org/10.1007/978-3-319-10587-1_7

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