About this Journal Submit a Manuscript Table of Contents
International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 247346, 11 pages
http://dx.doi.org/10.1155/2012/247346
Research Article

Onto: Ontological Context-Aware Model Based on 5W1H

Department of Computer and Radio Communications Engineering, Korea University, Seoul 136-701, Republic of Korea

Received 11 October 2011; Accepted 24 December 2011

Academic Editor: Tai Hoon Kim

Copyright © 2012 Jeong-Dong Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Ubiquitous computing is necessary to define models for broad contextual information arising out of surrounding environment. It also helps comprehend how to model a mechanism of selectively collecting useful pieces of contextual information and of providing relevant intelligent services. Further, studies are also required on how to process contextual information, its maintenance, and reasoning. However, current context-aware researches are still in need of modeling techniques reflecting ontological characteristics. As a result, it is impossible to effectively provide relevant intelligent services. They are limited as well in terms of contextual reasoning and interoperability across different pieces of contextual information. Aware of the issues, this study proposes an ontology-based context-aware modeling technique, along with a relevant framework, in order to enable efficient specification of contextual information and, thereby, further to provide intelligent context-aware services for context management and reasoning. Moreover, we mobilize the maxim of “five Ws and one H” to process physical and logical contextual information and to support our proposed technique. The maxim-applied modeling technique sets forth an intuitive context-aware schema and demonstrates high applicability to sharing and integration of contextual information. Meanwhile, the ontology-based modeling supports reasoning on contextual information and facilitates more intelligent and reliable services.