Abstract
Mobile professionals need to be assisted with suitable mobile GeoBI (Geospatial Business Intelligence) systems, which are able to capture, organize and structure the user’s reality into a relevant context model and reason on it. GeoBI context modelling and reasoning are still research issues since there is not yet either a model or a relevant taxonomy regarding GeoBI contextual information. To fill this gap, this paper proposes an extended and detailed OWL-based mobile GeoBI context ontology to provide context-aware applications and users with relevant contextual information and context-based reasoning capabilities. Context quality issues are handled an implementation architecture which is provided.
Highlights
In the today’s mobile, global, highly competitive, and technology-based business, mobile professionals deserve to get supported with suitable mobile Decision Support Systems (DSS) that we believe, should be 1) GeoBI (Geospatial Business Intelligence)-enabled to take into account geospatial features, and 2) context-based to cap
We propose to extend and detail that top-level UML-based model into an OWL (Web Ontology Language)-based context ontology to provide context-aware applications and users with more specific and precise contextual information and context-based reasoning capabilities
To analyze sales performance achieved by his salesmen in that location, Steve might want to get supported with mobile GeoBI services which are able to handle requests like: According to the current sales zone I’m in (e.g. WYNX sales Zone), what are the sales performed by the supervisors of the best performing salesman (e.g. John) of this quarter?
Summary
In the today’s mobile, global, highly competitive, and technology-based business, mobile professionals deserve to get supported with suitable mobile Decision Support Systems (DSS) that we believe, should be 1) GeoBI (Geospatial Business Intelligence)-enabled to take into account geospatial features, and 2) context-based to cap-. We propose to extend and detail that top-level UML-based model into an OWL (Web Ontology Language)-based context ontology to provide context-aware applications and users with more specific and precise contextual information and context-based reasoning capabilities. Given that location A (e.g. XYT museum) is located in B (e.g. District 0911) which is located in C (e.g. WYNX sales Zone), if a mobile device is located at XYT museum, it can derive that the salesman (e.g. Steve) using the device is located in WYNX sales zone To enable such reasoning, an inferable GeoBI context model is required. To ease its understanding and improve its readability, an OWL-compatible graphical formalism is provided by Cmap Tools COE [9] This one will be extended with geospatial and temporal pictograms to conveniently describe spatio-temporal concepts and will be used to design the proposed OWL-based mobile GeoBI context ontology.
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