Abstract
Efficiency and appeal of pervasive computing systems strongly depends on how well and robustly they represent and reason about context and situations. Populating situation search space and inferring situations from context which, in turn, is computed from fusing sensor data and observations remains a major research challenge. This paper proposes to use ontologies as representation of domain knowledge to generate situation search space and then match context with already defined situations. To illustrate the feasibility, a context spaces approach is used to represent, generate and reason about situations as abstractions in a multidimensional space. The proposed approach is evaluated and discussed.
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Anagnostopoulos, C., Ntarladimas, Y., Hadjiefthymiades, S.: Situational computing: an innovative architecture with imprecise reasoning. J. Syst. Softw. 80(12), 1993–2014 (2007)
Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A., Riboni, D.: A survey of context modelling and reasoning techniques. Pervasive Mob. Comput. 6(2), 161–180 (2010)
Barnaghi, P., Meissner, S., Presser, M., Moessner, K.: Sense and sens’ ability: semantic data modelling for sensor networks (2009)
Bazire, M., Brézillon, P.: Understanding context before using it. In: Leake, D.B., Kokinov, B., Dey, A.K., Turner, R. (eds.) CONTEXT 2005. LNCS (LNAI), vol. 3554, pp. 29–40. Springer, Heidelberg (2005). doi:10.1007/11508373_3
Boytsov, A., Zaslavsky, A.: Formal verification of context and situation models in pervasive computing. Pervasive Mob. Comput. 9(1), 98–117 (2013)
Chen, H., Finin, T., Joshi, A.: An ontology for context-aware pervasive computing environments. Spec. Issue Ontol. Distrib. Syst. Knowl. Eng. Rev. 18, 197–207 (2003)
Chen, H., Finin, T., Joshi, A.: The SOUPA ontology for pervasive computing. In: Tamma, V., Cranefield, S., Finin, T. (eds.) Ontologies for Agents: Theory and Experiences. Whitestein Series in Software Agent Technologies, pp. 233–258. Springer, Switzerland (2005)
Compton, M., Henson, C.A., Lefort, L., et al.: A survey of the semantic specification of sensors. In: CEUR Workshop Proceedings, October 2009
Calbimonte, J.P., Yan, Z., Jeung, H., et al.: Deriving semantic sensor metadata from raw measurements. In: 5th International Workshop on Semantic Sensor Networks, in conjunction with the 11th International Semantic Web Conference (ISWC), November 2012
Dapoigny, R., Barlatier, P.: Formalizing context for domain ontologies in Coq. In: Brézillon, P., Gonzalez, A.J. (eds.) Context in Computing, pp. 437–454. Springer, New York (2014)
Dey, A.K., Abowd, G.D.: Towards a better understanding of context and context-awareness. In: CHI 2000 Workshop on the What, Who, Where, When, and How of Context-Awareness, pp. 304–307 (2000)
Delir Haghighi, P., Krishnaswamy, S., Zaslavsky, A., Gaber, M.M.: Reasoning about context in uncertain pervasive computing environments. In: Tröster, G., Lombriser, C., Kortuem, G., Havinga, P., Roggen, D. (eds.) EuroSSC 2008. LNCS, vol. 5279, pp. 112–125. Springer, Heidelberg (2008)
Ejigu, D., Scuturici, M., Brunie, L.: An ontology-based approach to context modeling and reasoning in pervasive computing. In: Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops, IEEE Computer Society, pp. 14–19 (2007)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquis. 5(2), 199–220 (1993)
Gu, T., Pung, H.K., Zhang, D.Q.: A service-oriented middleware for building context-aware services. J. Netw. Comput. Appl. 28(1), 1–18 (2005)
Padovitz, A., Loke, S.W., Zaslavsky, A., Burg, B.: Verification of uncertain context based on a theory of context spaces. Int. J. Pervasive Comput. Commun. 3(1), 30–56 (2007)
Wang, X.H., Zhang, D.Q., Gu, T., Pung, H.K.: Ontology based context modeling and reasoning using OWL. In: Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops, pp. 18–22 (2004)
Ye, J., Coyle, L., Dobson, S., Nixon, P.: Ontology-based models in pervasive computing systems. Knowl. Eng. Rev. 22(4), 315–347 (2007)
Ye, J., Dobson, S., McKeever, S.: Situation identification techniques in pervasive computing: a review. Pervasive Mob. Comput. 8(1), 36–66 (2012)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
w3.org: Semantic sensor network XG final report: w3c incubator group report. http://www.w3.org/2005/Incubator/ssn/XGR-ssn-20110628/, June 2011. Accessed 14 Aug 2015
OGC observations and measurements: http://www.opengeospatial.org/standards/om. Accessed 14 Aug 2015
Protégé ontology editor: http://protege.stanford.edu/. Accessed 14 Aug 2015
SPARQL 1.1 overview: http://www.w3.org/TR/sparql11-overview/. Accessed 14 Aug 2015
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Boytsov, A., Zaslavsky, A., Eryilmaz, E., Albayrak, S. (2015). Situation Awareness Meets Ontologies: A Context Spaces Case Study. In: Christiansen, H., Stojanovic, I., Papadopoulos, G. (eds) Modeling and Using Context. CONTEXT 2015. Lecture Notes in Computer Science(), vol 9405. Springer, Cham. https://doi.org/10.1007/978-3-319-25591-0_1
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DOI: https://doi.org/10.1007/978-3-319-25591-0_1
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