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Conference Papers Year : 2017

Strider R: Massive and Distributed RDF Graph Stream Reasoning

Olivier Curé
Hubert Naacke
Ke Li
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Abstract

Reasoning over semantically annotated data is an emerging trend in stream processing aiming to produce sound and complete answers to a set of continuous queries. It usually comes at the cost of finding a trade-off between data throughput and the cost of expressive inferences. Strider R proposes such a trade-off and combines a scalable RDF stream processing engine with an efficient reasoning system. The main reasoning tasks are based on a query rewriting approach for SPARQL that benefits from an intelligent encoding of an extension of the RDFS (i.e., RDFS with owl:sameAs) ontology elements. Strider R runs in production at a major international water management company to detect anomalies from sensor streams. The system is evaluated along different dimensions and over multiple datasets to emphasize its performance.
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Dates and versions

hal-01657494 , version 1 (06-12-2017)

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Xiangnan Ren, Olivier Curé, Hubert Naacke, Jérémy Lhez, Ke Li. Strider R: Massive and Distributed RDF Graph Stream Reasoning. IEEE International Conference on Big Data, Big Data 2017, Dec 2017, Boston, United States. pp.3358-3367, ⟨10.1109/BigData.2017.8258321⟩. ⟨hal-01657494⟩
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