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has been cited by the following article:

• TITLE: An OWL-Based Mobile GeoBI Context Ontology Enabling Location-Based and Context-Based Reasoning and Supporting Contextual Business Analysis

  AUTHORS: Belko Abdoul Aziz Diallo, Thierry Badard, Frédéric Hubert, Sylvie Daniel

  KEYWORDS: Mobile Geospatial Business Intelligence (GeoBI), Context Modelling, Context Ontology, Context Awareness, Context Reasoning, Location-Based Reasoning

  JOURNAL NAME: International Journal of Geosciences, Vol.6 No.1, January 30, 2015

  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.