Tuesday, December 19, 2006
Towards an extensible context ontology for Ambient Intelligence
Towards an extensible context ontology for
Ambient Intelligence (PDF file)
by Davy Preuveneers, Jan Van den Bergh, Dennis Wagelaar, Andy Georges,
Peter Rigole, Tim Clerckx, Yolande Berbers, Karin Coninx, Viviane
Jonckers, and Koen De Bosschere
"Context-awareness is a hot research domain, with interesting topics such as
context modeling, formal context languages for specifying facts and interrelationships, and infrastructure support for querying and reasoning on contextual information using an inference engine.
The Context Ontology Language (CoOL) [3] is an ontology-based context modeling approach, which uses the Aspect-Scale-Context (ASC) model where each aspect (e.g. spatial distance) can have several scales (e.g. kilometer scale or mile scale) to express some context information (e.g. 20). Mapping functions exist to convert context information from one scale to another. CoOL is very useful for describing concepts with an inherent metric ordering such as in requirement R.2, though less practical for expressing scales for aspects as in requirement R.1. Chen et al. [4] propose a context broker architecture (CoBrA) using an ontology to describe persons, places and intentions. Less emphasis is put on the notion of services and related aspects, such as user interfaces and mobile devices on which these services are deployed, needed to fulfill the above requirements. Gu et al. [5] present a service-oriented context-aware middleware (SOCAM) based on a context model with person, location, activity and computational entity (such as a device, network, application, service, etc.) as basic context concepts. The notion of mobile services seems to be beyond the scope of this context model. Henricksen and Indulska [6] propose a context model that describes context based on several types of facts (e.g. sensed, static and profiled) subject to constraints and quality annotations."
Ambient Intelligence (PDF file)
by Davy Preuveneers, Jan Van den Bergh, Dennis Wagelaar, Andy Georges,
Peter Rigole, Tim Clerckx, Yolande Berbers, Karin Coninx, Viviane
Jonckers, and Koen De Bosschere
"Context-awareness is a hot research domain, with interesting topics such as
context modeling, formal context languages for specifying facts and interrelationships, and infrastructure support for querying and reasoning on contextual information using an inference engine.
The Context Ontology Language (CoOL) [3] is an ontology-based context modeling approach, which uses the Aspect-Scale-Context (ASC) model where each aspect (e.g. spatial distance) can have several scales (e.g. kilometer scale or mile scale) to express some context information (e.g. 20). Mapping functions exist to convert context information from one scale to another. CoOL is very useful for describing concepts with an inherent metric ordering such as in requirement R.2, though less practical for expressing scales for aspects as in requirement R.1. Chen et al. [4] propose a context broker architecture (CoBrA) using an ontology to describe persons, places and intentions. Less emphasis is put on the notion of services and related aspects, such as user interfaces and mobile devices on which these services are deployed, needed to fulfill the above requirements. Gu et al. [5] present a service-oriented context-aware middleware (SOCAM) based on a context model with person, location, activity and computational entity (such as a device, network, application, service, etc.) as basic context concepts. The notion of mobile services seems to be beyond the scope of this context model. Henricksen and Indulska [6] propose a context model that describes context based on several types of facts (e.g. sensed, static and profiled) subject to constraints and quality annotations."
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