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Ontology-based context modeling in service-oriented computing: A systematic mapping
dc.contributor.author | Cabrera Bejar, Oscar Jair |
dc.contributor.author | Franch Gutiérrez, Javier |
dc.contributor.author | Marco Gómez, Jordi |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Ciències de la Computació |
dc.date.accessioned | 2017-06-23T06:58:41Z |
dc.date.available | 2019-05-10T00:30:43Z |
dc.date.issued | 2017-05-10 |
dc.identifier.citation | Cabrera, O., Franch, X., Marco, J. Ontology-based context modeling in service-oriented computing: A systematic mapping. "Data and knowledge engineering", Juliol 2017, vol. 110. p. 24-53 |
dc.identifier.issn | 0169-023X |
dc.identifier.uri | http://hdl.handle.net/2117/105746 |
dc.description.abstract | Context: Service-oriented computing and context-aware computing are two consolidated paradigms that are changing the way of providing and consuming software services. Whilst service-oriented computing is based on service-oriented architectures for providing flexible software services, context-aware computing articulates different phases of a context life cycle for changing the behavior of such services. The synergy between both paradigms provides the context to this study. Objective: This study analyzes the current state of the art of context models, specifically: (1) which are these proposals and how are they related; (2) what are their structural characteristics; (3) what context information is the most addressed; and (4) what are their most consolidated definitions. Given their dominance on the field, the study focuses on ontology-based approaches. Method: We conducted a systematic mapping by establishing a review protocol that integrates automatic and manual searches from different sources. We applied a rigorous method to elicit the keywords from the research questions and selection criteria to retrieve the papers to evaluate. Results: Overall, 138 primary studies were selected to answer our research questions. These proposals were studied in depth by analyzing: 1) distribution along time and their relationships; 2) size correlated with the number of classes and levels of the context model, and coverage of the definitions provided as indicator of quality provided; 3) most addressed context information; 4) most consolidated definitions of context information. Conclusions: The contribution of this survey is to make available a unified and consolidated body of knowledge on context for service-oriented computing that could be instantiated and used as starting point in a variety of use cases. This sweeping view on the anatomy of context models may help avoiding the postulation of new proposals not aligned with the current research. |
dc.language.iso | eng |
dc.publisher | Elsevier |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Enginyeria del software |
dc.subject.lcsh | Service-oriented architecture (Computer science) |
dc.subject.lcsh | Electronic data processing -- Distributed processing |
dc.subject.other | Context-aware computing |
dc.subject.other | Context modeling |
dc.subject.other | Ontology |
dc.subject.other | Service-oriented computing |
dc.subject.other | Systematic mapping |
dc.title | Ontology-based context modeling in service-oriented computing: A systematic mapping |
dc.type | Article |
dc.subject.lemac | Arquitectura orientada a serveis (Informàtica) |
dc.subject.lemac | Processament distribuït de dades |
dc.contributor.group | Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering |
dc.identifier.doi | 10.1016/j.datak.2017.03.008 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.sciencedirect.com/science/article/pii/S0169023X16301380 |
dc.rights.access | Open Access |
local.identifier.drac | 20329501 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/644018/EU/SUpporting evolution and adaptation of PERsonalized Software by Exploiting contextual Data and End-user feedback/SUPERSEDE |
local.citation.author | Cabrera, O.; Franch, X.; Marco, J. |
local.citation.publicationName | Data and knowledge engineering |
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