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Towards Ontology-Based Event Processing

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Abstract

The rapid change and heterogeneity of today’s generated data calls for real-time decision making systems that can cope with the presented heterogeneity. In this paper, we present an Ontology Based Event Processing system that bridges the gap between ontology-based reasoning and event processing. We propose both a language and an architecture to perform event processing over abstract ontology concepts. This allows to perform efficient temporal reasoning, while the high-level ontological definitions reduce the need for knowledge of the underlying data structure in complex domains.

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Notes

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  2. 2.

    The semantics of these operators is similar to a left, right or full -join but their selectivity depends on how the constituents are temporally related.

  3. 3.
  4. 4.

    Not can be used only as a combination of other patterns.

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  6. 6.

    The code is part of the new version of MASSIF platform which is not yet available as open source. A stand alone version will be published athttps://github.com/IBCNServices/OBEP.

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  8. 8.

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Author information

Authors and Affiliations

  1. imec, Ghent University, Ghent, Belgium

    Riccardo Tommasini, Pieter Bonte, Emanuele Della Valle, Erik Mannens, Filip De Turck & Femke Ongenae

  2. DEIB, Politecnico di Milano, Milan, Italy

    Riccardo Tommasini, Pieter Bonte, Emanuele Della Valle, Erik Mannens & Femke Ongenae

Authors
  1. Riccardo Tommasini

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  2. Pieter Bonte

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  3. Emanuele Della Valle

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  4. Erik Mannens

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  5. Filip De Turck

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  6. Femke Ongenae

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Corresponding author

Correspondence toPieter Bonte.

Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler, Povo, Trento, Italy

    Mauro Dragoni

  2. Universitad Politecnica de Madrid, Madrid, Spain

    María Poveda-Villalón

  3. University of Oslo, Oslo, Norway

    Ernesto Jimenez-Ruiz

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© 2017 Springer International Publishing AG

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Tommasini, R., Bonte, P., Della Valle, E., Mannens, E., De Turck, F., Ongenae, F. (2017). Towards Ontology-Based Event Processing. In: Dragoni, M., Poveda-Villalón, M., Jimenez-Ruiz, E. (eds)OWL: Experiences and Directions – Reasoner Evaluation. OWLED ORE 2016 2016. Lecture Notes in Computer Science(), vol 10161. Springer, Cham. https://doi.org/10.1007/978-3-319-54627-8_9

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JPY 5719
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