A semantic web based system for context metadata management

Abstract

With the increasing usage of embedded systems and sensors in our surroundings, a new type of information systems - context aware systems - are gaining importance. These user-centric systems acquire context information which describes the state of the user and the user environment, and offer adaptable and personalized services based on the user context information. The central part of a context aware system is the context model used for describing user context information. The context information originates from a multitude of heterogeneous sources, such as personal calendars, sensors attached to the users or to the user's environment and Web based sources, such as social networking sites. The information from these sources is typically on different abstraction levels and is organized according to different data models. This work proposes a Semantic Web based context metadata management system. The first part of the work develops an ontology model for user context. The user context model integrates information from multiple and heterogeneous sources which are modeled largely by reusing existing well accepted ontologies. The second part of the work proposes a method to infer and reason about additional user context information based on the available context information using rules and ontologies. We instantiate and evaluate the proposed system by performing a social networking case study called meetFriends. In this application, information is collected from various sources such as sensors attached to the users and public web sources - YellowPages. The moods of the users are inferred from a set of rules. A meeting between two users can be set up based on the moods, locations and preferences of the users. The results indicate that Semantic Web technologies are well suited for integrating various data sources, processing of user context information, and enabling adaptable and personalized services. © 2009 Springer-Verlag Berlin Heidelberg.