research-article

3LConOnt: a three-level ontology for context modelling in context-aware computing

Authors:

Jordi MarcoAuthors Info & Claims

Volume 18, Issue 2

Pages 1345 - 1378

https://doi.org/10.1007/s10270-017-0611-z

Published: 01 April 2019 Publication History

Abstract

Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution.

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cover image Software and Systems Modeling (SoSyM)

Software and Systems Modeling (SoSyM) Volume 18, Issue 2

Apr 2019

766 pages

ISSN:1619-1366

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Copyright © 2019 Springer-Verlag GmbH Germany, part of Springer Nature.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 April 2019

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Cited By

Sonfack Sounchio SKamsu-Foguem BGeneste L(2023)Construction of a base ontology to represent accident expertise knowledgeCognition, Technology and Work10.1007/s10111-023-00724-825:2-3(183-201)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1007/s10111-023-00724-8
do Nascimento Lde Oliveira J(2023)An Ontology for Context Modeling in Smart SpacesConceptual Modeling10.1007/978-3-031-47262-6_19(354-371)Online publication date: 6-Nov-2023
https://dl.acm.org/doi/10.1007/978-3-031-47262-6_19
Nagowah SBen Sta HGobin-Rahimbux B(2021)A systematic literature review on semantic models for IoT-enabled smart campusApplied Ontology10.3233/AO-20024016:1(27-53)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.3233/AO-200240
Cabrera OOriol MFranch XMarco J(2021)A context-aware monitoring architecture for supporting system adaptation and reconfigurationComputing10.1007/s00607-021-00923-z103:8(1621-1655)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s00607-021-00923-z
Henarejos-Blasco JGarcía-Díaz JApolinario-Arzube ÓValencia-García Rde Castro APinto JChagas do Nascimento RFelici-Castell SSamper Zapater J(2020)CNL-RDF-queryProceedings of the 10th Euro-American Conference on Telematics and Information Systems10.1145/3401895.3402064(1-5)Online publication date: 25-Nov-2020
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Franch XSeyff NOriol MFricker SGroher IVierhauser MWimmer M(2020)Towards Integrating Data-Driven Requirements Engineering into the Software Development Process: A Vision PaperRequirements Engineering: Foundation for Software Quality10.1007/978-3-030-44429-7_10(135-142)Online publication date: 24-Mar-2020
https://dl.acm.org/doi/10.1007/978-3-030-44429-7_10

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