Title: An approach based on the clustering of spatial requirements' models and MDA to design spatial data warehouses
Authors: Sana Ezzedine; Sami Yassine Turki; Sami Faiz
Addresses: LTSIRS Laboratory, National School of Engineers, BP 37, Campus Universitaire El Manar, Tunis, Tunisia ' LTSIRS Laboratory, National School of Engineers, BP 37, Campus Universitaire El Manar, Tunis, Tunisia ' LTSIRS Laboratory, National School of Engineers, BP 37, Campus Universitaire El Manar, Tunis, Tunisia
Abstract: 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.
Keywords: spatial data warehouses; model driven architecture; MDA; decision maker requirements; k-means clustering; query view transformations; QVT; data mining; spatial requirements.
International Journal of Data Mining, Modelling and Management, 2015 Vol.7 No.4, pp.276 - 292
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 24 Dec 2015 *