In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatia...In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.展开更多
With the requirements for high performance results in the today’s mobile, global, highly competitive, and technology-based business world, business professionals have to get supported by convenient mobile decision su...With the requirements for high performance results in the today’s mobile, global, highly competitive, and technology-based business world, business professionals have to get supported by convenient mobile decision support systems (DSS). To give an improved support to mobile business professionals, it is necessary to go further than just allowing a simple remote access to a Business Intelligence platform. In this paper, the need for actual context-aware mobile Geospatial Business Intelligence (GeoBI) systems that can help capture, filter, organize and structure the user mobile context is exposed and justified. Furthermore, since capturing, structuring, and modeling mobile contextual information is still a research issue, a wide inventory of existing research work on context and mobile context is provided. Then, step by step, we methodologically identify relevant contextual information to capture for mobility purposes as well as for BI needs, organize them into context-dimensions, and build a hierarchical mobile GeoBI context model which (1) is geo-spatial-extended, (2) fits with human perception of mobility, (3) takes into account the local context interactions and information-sharing with remote contexts, and (4) matches with the usual hierarchical aggregated structure of BI data.展开更多
文摘In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.
文摘With the requirements for high performance results in the today’s mobile, global, highly competitive, and technology-based business world, business professionals have to get supported by convenient mobile decision support systems (DSS). To give an improved support to mobile business professionals, it is necessary to go further than just allowing a simple remote access to a Business Intelligence platform. In this paper, the need for actual context-aware mobile Geospatial Business Intelligence (GeoBI) systems that can help capture, filter, organize and structure the user mobile context is exposed and justified. Furthermore, since capturing, structuring, and modeling mobile contextual information is still a research issue, a wide inventory of existing research work on context and mobile context is provided. Then, step by step, we methodologically identify relevant contextual information to capture for mobility purposes as well as for BI needs, organize them into context-dimensions, and build a hierarchical mobile GeoBI context model which (1) is geo-spatial-extended, (2) fits with human perception of mobility, (3) takes into account the local context interactions and information-sharing with remote contexts, and (4) matches with the usual hierarchical aggregated structure of BI data.
