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Authors: Farah Karim 1 ; Maria-Esther Vidal 2 and Sören Auer 3

Affiliations: 1 Enterprise Information Systems (EIS) and University of Bonn, Germany ; 2 Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Germany ; 3 Enterprise Information Systems (EIS), University of Bonn and Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Germany

ISBN: 978-989-758-246-2

Keyword(s): Sensor, Linked Data, Data Factorization, Query Optimization and Execution.

Abstract: Large collections of sensor data are semantically described using ontologies, e.g., the Semantic Sensor Network (SSN) ontology. Semantic sensor data are RDF descriptions of sensor observations from related sampling frames or sensors at multiple points in time, e.g., climate sensor data. Sensor values can be repeated in a sampling frame, e.g., a particular temperature value can be repeated several times, resulting in a considerable increase in data volume. We devise a factorized compact representation of semantic sensor data using linked data technologies to reduce repetition of same sensor values, and propose algorithms to generate collections of factorized semantic sensor data that can be managed by existing RDF triple stores. We empirically study the effectiveness of the proposed factorized representation of semantic sensor data. We show that the size of semantic sensor data is reduced by more than 50\% on average without loss of information. Further, we have evaluated the impact o f this factorized representation of semantic sensor data on query execution. Results suggest that query optimizers can be empowered with semantics from factorized representations to generate query plans that effectively speed up query execution time on factorized semantic sensor data. (More)

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Paper citation in several formats:
Karim, F.; Vidal, M. and Auer, S. (2017). Efficient Processing of Semantically Represented Sensor Data.In Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-246-2, pages 252-259. DOI: 10.5220/0006287002520259

@conference{webist17,
author={Farah Karim. and Maria{-}Esther Vidal. and Sören Auer.},
title={Efficient Processing of Semantically Represented Sensor Data},
booktitle={Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2017},
pages={252-259},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006287002520259},
isbn={978-989-758-246-2},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Efficient Processing of Semantically Represented Sensor Data
SN - 978-989-758-246-2
AU - Karim, F.
AU - Vidal, M.
AU - Auer, S.
PY - 2017
SP - 252
EP - 259
DO - 10.5220/0006287002520259

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