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An approach based on the clustering of spatial requirements' models and MDA to design spatial data warehouses

A survey of existing literature reveals that all proposed approaches have not considered decision makers' requirements in the design of spatial data warehouses. In the present paper, we propose a model driven architecture-based approach to design spatial data warehouses that integrates spatial and descriptive needs of several decision makers. We start by identifying spatial and descriptive decision maker's requirements. We use the formalism of the computation independent model to describe these requirements. Then, we extend the clustering algorithm k-means to classify decision makers' models. Finally, we develop and apply a set of query view transformations to transit from each requirements model to the design of the corresponding spatial data warehouse. A case study which applies the different steps of our approach is presented.