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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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.
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Not can be used only as a combination of other patterns.
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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 at https://github.com/IBCNServices/OBEP.
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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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DOI: https://doi.org/10.1007/978-3-319-54627-8_9
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