An Ontology for Spatial Relevant Objects in a Location-aware System: Case Study: A Tourist Guide System

Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.




References:
[1] O. Achilleos A.,Yang K., Georgalas N, 2010. Context modeling and a
context-aware framework for pervasive service creation: A model-driven
approach. Journal of Pervasive and Mobile Computing., Vol. 6, p.p:
281-296.
[2] Audi, R., 1995, The Cambridge Dictionary of Philosophy (Cambridge:
Cambridge University Press).
[3] Agarwal, P., 2005, Ontological considerations in GIScience,
International Journal of Geographical Information Science Vol. 19, No.
5, 501-536.
[4] Dey A, Abowd G., 2000, Towards a better understanding of context and
context-awareness. Workshop on the What, Who, Where, When and
How of Context-Anwareness at CHI.
[5] Chaari T., Ejigu D., Laforest F. and Scuturici V., 2007. A
comprehensive approach to model and use context for adapting
applications in pervasive environments. Journal of Systems and
Software archive, 80(12): 1973-1992.
[6] Fritsch, D., & Volz, S. (2003). NEXUS - the mobile GIS-environment.
Proc. Joint First Workshop on Mobile Future and Symposium on Trends
in Communications pp. 1-4.
[7] Henricksen K, Indulska J, Rakotonirainy A., 2001, Infrastructure for
pervasive computing: challenges Workshop on Pervasive Computing
INFORMATIK 01, Viena, Austaria.
[8] Geake V., 2000. Web mapping. Get mobile, it-s the place to be, GIS
Europe. http:// www.geoplace.com./ge/2000/0900/0900mob.asp
[9] Gua, T Punga, H.K. and Zhang D.Q., 2005, A service-oriented
middleware for building context-aware services, Journal of Network and
Computer Applications 28 (2005) 1-18.
[10] Guarino, N., Formal ontology and information systems, In Proceedings
of the 1st International Conference on Formal Ontologies in Information
Systems, IOS Press, Trento, Italy, 1998.
[11] Guarino, N. and Giaretta, P., 1995, Ontologies and knowledge bases:
towards a terminological clarification. In N. Mars (Ed.), Towards Very
Large Knowledge Bases: Knowledge Building and Knowledge Sharing,
pp. 25-32 (Amsterdam: IOS Press).
[12] Jiang X. and Tan, A.H, 2009, Learning and inferencing in user ontology
for personalized Semantic Web search, Information Sciences 179 , p.p:
2794-2808.
[13] Kwon O. and Shin M.K., 2007. LACO: A location-aware cooperative
query system for securely personalized services, Expert Systems with
Applications, 34(4): 2966-2975.
[14] Liu, X. and Karimi H.A., 2006, Location awareness through trajectory
prediction, Journal of Computers, Environment and Urban Systems 30
(2006) 741-756.
[15] Leonhardt, U. 1998. Supporting Location-Awareness in Open
Distributed Systems". PhD Thesis, Department of Computing, Imperial
College of Science, University of London. 1998.
[16] Mann, W.R., 2000, The Discovery of Things: Aristotle-s Categories and
their Context Princeton, NJ: Princeton University Press.
[17] Neches, R., Fikes, R., Finin, T., Gruber, T., Senator, T. and Swartout,
W., 1991, Enabling technology for knowledge sharing. AI Magazine,
12, pp. 36-56.
[18] Raper J., Dykes J., Wood J., Mountain D., Krause A. and Rhind D.,
2002. A framework for evaluating geospatial information, Journal of
Information Sciense, 28(1):39-50.
[19] Reichenbacher T., 2005. The Concept of Relevance in Mobile Maps,
Location Based Services & Telecartography,
[20] Renz, J. 2001. A spatial odyssey of the interval algebra: Directed
intervals. In B. Nebel (ed.), Proc. of the 17th Znt 'I Joint Con on AI: 5 1-
56. Seattle: Morgan Kaufmann, Edited by Georg Gartner, Vienna
University of Technology, pp.41-46.
[21] Saracevic T., 1996, Relevance reconsidered, Proceeding, The Second
Conference on Conceptions of Library and Information Science
(CoLIS2), pp.210-218.
[22] Schmidt, A. 2002. Ubiquitous Computing - Computing in Context,
PhD Thesis, Lancaster University.
[23] Smith M, Welty C, McGuinness D. Web Ontology Language (OWL)
Guide, August 2003. The Open Services Gateway Initiative (OSGi),
www.osgi.org
[24] Strang, T., Linnhoff-Popien, C., 2004. A context modelling survey. In:
Workshop on Advanced Context Modelling, Reasoning and
Management associated with the Sixth International Conference on
Ubiquitous Computing (UbiComp4). Nottingham/England.
[25] Streefkerk J.W, Esch-Bussemakers M.P, Neerincx M.A., 2006,
Computers in Human Behavior, p.p:749-770, Designing personal
attentive user interfaces in the mobile public safety domain.
[26] Sowa, J.F., 2000, Knowledge Representation. Logical, Philosophical
and Computational Foundations, Pacific Grove, CA: Brooks/Cole.
[27] Vieira V., Tedesco P. and Salgado A.C., 2010. Designing contextsensitive
systems: An integrated approach. Journal of Expert Systems
with Applications.