Strider R: Massive and Distributed RDF Graph Stream Reasoning

Xiangnan Ren; Olivier Curé; Hubert Naacke; Jérémy Lhez; Ke Li

Strider R: Massive and Distributed RDF Graph Stream Reasoning

Xiangnan Ren ^{1, 2} Olivier Curé ¹ Hubert Naacke ³ Jérémy Lhez ¹ Ke Li ²

1 LIGM - Laboratoire d'Informatique Gaspard-Monge

2 Atos

3 BD - Bases de Données

LIP6 - Laboratoire d'Informatique de Paris 6

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.

Document type :

Conference papers

Domain :

Computer Science [cs] / Databases [cs.DB]

Computer Science [cs] / Distributed, Parallel, and Cluster Computing [cs.DC]

Complete list of metadatas

https://hal.sorbonne-universite.fr/hal-01657494
Contributor : Hubert Naacke <>
Submitted on : Wednesday, December 6, 2017 - 5:56:44 PM
Last modification on : Friday, March 22, 2019 - 9:43:52 AM

Strider R: Massive and Distributed RDF Graph Stream Reasoning

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