research-article

Semantic Exploration of Sensor Data

Authors:

Snehasis Banerjee,

Abhishek Mishra,

Ranjan DasguptaAuthors Info & Claims

Web-KR '14: Proceedings of the 5th International Workshop on Web-scale Knowledge Representation Retrieval & Reasoning

Pages 55 - 58

https://doi.org/10.1145/2663792.2663800

Published: 03 November 2014 Publication History

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Abstract

With governments and administrations releasing open linked data, and with the gradual rise of sensor deployments across the world, semantic queries on the combined sensor and linked data has become a need to provide several intelligent smart city services and applications. The data is represented in form of triples (RDF), concepts and relations in form of ontologies (OWL) and the corresponding query language is SPARQL as per standards of Semantic Web. In this paper, a system for sensor exploration is presented, which takes a set of keywords, context, data, learned and background knowledge as input and produces the intentioned result as output. The system tries to keep the underlying semantic web technologies transparent to the end user. The relevant challenges and the scope of future work is also discussed.

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Banerjee SChattopadhyay TPal AGarain U(2018)Automation of feature engineering for IoT analyticsACM SIGBED Review10.1145/3231535.323153815:2(24-30)Online publication date: 5-Jun-2018
https://dl.acm.org/doi/10.1145/3231535.3231538
Qanbari SBehinaein NRahimzadeh RDustdar S(2015)GaticaProceedings of the 2015 3rd International Conference on Future Internet of Things and Cloud10.1109/FiCloud.2015.37(38-43)Online publication date: 24-Aug-2015
https://dl.acm.org/doi/10.1109/FiCloud.2015.37
Zeng YKotoulas SHuang ZLi JWang XGarofalakis MSoboroff ISuel TWang M(2014)Web-KR 2014Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2663545(2102-2103)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2661829.2663545

Index Terms

Semantic Exploration of Sensor Data
1. Information systems

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Web-KR '14: Proceedings of the 5th International Workshop on Web-scale Knowledge Representation Retrieval & Reasoning

November 2014

72 pages

ISBN:9781450316064

DOI:10.1145/2663792

Program Chairs:
Yi Zeng
Chinese Academy of Sciences, China
,
Spyros Kotoulas
IBM Research, Ireland
,
Zhisheng Huang
VU University Amsterdam, The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

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Published: 03 November 2014

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November 3, 2014

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Banerjee SChattopadhyay TPal AGarain U(2018)Automation of feature engineering for IoT analyticsACM SIGBED Review10.1145/3231535.323153815:2(24-30)Online publication date: 5-Jun-2018
https://dl.acm.org/doi/10.1145/3231535.3231538
Qanbari SBehinaein NRahimzadeh RDustdar S(2015)GaticaProceedings of the 2015 3rd International Conference on Future Internet of Things and Cloud10.1109/FiCloud.2015.37(38-43)Online publication date: 24-Aug-2015
https://dl.acm.org/doi/10.1109/FiCloud.2015.37
Zeng YKotoulas SHuang ZLi JWang XGarofalakis MSoboroff ISuel TWang M(2014)Web-KR 2014Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2663545(2102-2103)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2661829.2663545

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Using the relation ontology Metarel for modelling Linked Data as multi-digraphs

RDF, Jena, SparQL and the 'Semantic Web'

Querying semantic web data with SPARQL

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