4. CONCLUSION 
Ontological approach including concepts, relations and 
instances is essential for smart environments like LBS. This 
paper presents a simple spatial ontology in order to provide a 
location sensitive context aware computing system. System 
enables a solution for finding closest place at the smart 
environments. The solution differs from distance based 
solutions because of its applicable data structure to an 
ontological context aware system. 
This ontological structure should be extended to handle more 
LBS components such as navigation and meeting queries. 
Ontological inferences provide implicit context so as to obtain 
additional information about the situation. 
Statistical analyses of the ontological concepts and their 
relations have not been completed yet. After the analysis, some 
obvious benefits of the knowledge base also will be shown 
later. This paper also ignores roads to determine closest place. 
To obtain more accurate result road entity should be also added 
to knowledge base. 
REFERENCES 
Chen, H., Finin, T. and Joshi, A., 2004. An ontology for context 
aware pervasive computing environments. Knowledge 
Engineering Review 18, pp. 197-207. 
Christopoulou, E., Goumopoulos, C., Zaharakis, I. and Kameas, 
A., 2004. An ontology-based conceptual model for composing 
context-aware applications. Workshop on advanced context 
modeling, reasoning and management, 6th International 
Conference on ubiquitous computing, Nottingham, England. 
Dey, A. and Abowd, G., 2000. Towards a better understanding 
of context and context-awareness. CHI'2000 Workshop on the 
What, Who, Where and How of Context Awareness, The 
Hague, The Netherlands. 
Gu, T., Wang, X., Pung, H. and Zhang, D., 2004. An ontology 
based context model in intelligent environments. Proceeding of 
Communication Network and Distributed Systems Modeling 
and Simulation Conference, San Diego, California, USA. 
Hong, D., Kim, D., Yun, J. and Han, K., 2005. An adaptive 
location data management strategy for context-awareness in the 
ubiquitous — computing environment. Proceedings of 
International Symposium on Spatio-temporal Modeling, Spatial 
Reasoning, Spatial Analysis, Data Mining and Data Fusion, 
Beijing, China pp. 57-62. 
Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, 
B. and Dean, M., 2004. SWRL: A semantic web rule language 
combining OWL and RuleML, 
http://www.w3org/Submission/SWRL, May 2004. 
Kim, J., Kim, J., Hwang, H. and Kim, C., 2005. Location 
sensitive tour guide services using the semantic web. Lecture 
Notes in Computer Sciences 3682, pp. 908—914. 
Lutz, M. and Klien, E., 2006. Ontology-based retrieval of 
geographic information. International Journal of Geographical 
Information Science 20, pp. 233-260. 
484 
McGuinness, D.L. and van Harmelen, F., 2004. OWL web 
ontology language overview, W3C Recommendation, 
http://www.w3.org/TR/owl-features/, 2004. 
Weissenberg, N., Gartmann, R. and Voisard, A., 2006. An 
ontology-based approach to personalized  situation-aware 
mobile service. Geolnformatica 10, pp. 55-90. 
Zhu, F., Mutka, M. and Ni, L., 2005. Service discovery in 
pervasive computing environments. Pervasive Computing 4, pp. 
81-90.