Semantic web technologies in pervasive computing : a survey and research roadmap

Pervasive and sensor-driven systems are by nature open and extensible, both in terms of input and tasks they are required to perform. Data streams coming from sensors are inherently noisy, imprecise and inaccurate, with differing sampling rates and complex correlations with each other. These characteristics pose a significant challenge for traditional approaches to storing, representing, exchanging, manipulating and programming with sensor data. Semantic Web technologies provide a uniform framework for capturing these properties. Offering powerful representation facilities and reasoning techniques, these technologies are rapidly gaining attention towards facing a range of issues such as data and knowledge modelling, querying, reasoning, service discovery, privacy and provenance. This article reviews the application of the Semantic Web to pervasive and sensor-driven systems with a focus on information modelling and reasoning along with streaming data and uncertainty handling. The strengths and weaknesses of current and projected approaches are analysed and a roadmap is derived for using the Semantic Web as a platform, on which open, standard-based, pervasive, adaptive and sensor-driven systems can be deployed.

Citation

Ye , J , Dasiopoulou , S , Stevenson , G T , Meditskos , G , Kontopoulos , E , Kompatsiaris , I & Dobson , S A 2015 , ' Semantic web technologies in pervasive computing : a survey and research roadmap ' , Pervasive and Mobile Computing , vol. 23 , pp. 1-25 . https://doi.org/10.1016/j.pmcj.2014.12.009

Publication

Pervasive and Mobile Computing

Status

Peer reviewed

DOI

https://doi.org/10.1016/j.pmcj.2014.12.009

ISSN

1574-1192

Type

Journal article

Rights

© 2014. Elsevier B.V. All rights reserved. This is the author’s version of a work that was accepted for publication in Pervasive and Mobile Computing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pervasive and Mobile Computing, 9 January 2015 DOI 10.1016/j.pmcj.2014.12.009

Description

This work has been supported by the EU FP7 projects SAPERE: Self-aware Pervasive Service Ecosystems under Contract No. 256873 and Dem@Care: Dementia Ambient Care — Multi-Sensing Monitoring for Intelligent Remote Management and Decision Support under Contract No. 288199.