Existing Spatial OLAP (SOLAP) applications are targeted towards desktop computer environments. In order to enable geospatial decision support in mobility contexts, SOLAP requires some modifications. This paper describes a solution, based on service-oriented architectures and Web services technologies, designed to adapt SOLAP data cubes to the requirements and constraints encountered in mobile c...

Different proposals of SOLAP query languages exist in the literature; however, a taxonomy of SOLAP operators has not been formally defined to date. This paper presents a systematic method for classifying SOLAP operators which combines the elements that constitute a data cube with three application categories: multidimensional, spatial and temporal. Additionally, this paper proposes a set of SOL...

RÉSUMÉ. La généralisation à la volée désigne l’utilisation de techniques de généralisation automatique en temps réel. Les données générées sont temporaires et exclusivement destinées à la visualisation et non pas au stockage ou à d’autres fins. Ceci, rend ce processus bien adapté aux contextes hautement interactifs tels que la cartographie en ligne et le SOLAP. BLG tree et GAP tree sont des str...

Spatial OLAP (SOLAP) systems do not completely integrate visualization, interaction and analysis functionalities of Geographic Information Systems. In this paper, we propose a flexible Web SOLAP tool, GoOlap, which combines OLAP and Geovisualization functionalities through the integration of the geobrowser Google Earth and the OLAP tool Mondrian/JPivot. Google Earth enriches spatio-multidimensi...

To support their analytical processes, today's organizations deploy data warehouses and client tools such as OLAP (On-Line Analytical Processing) to access, visualize, and analyze their integrated, aggregated and summarized data. Since a large part of these data have a spatial component, better client tools are required to take full advantage of the geometry of the spatial phenomena or objects ...

Spatial On-Line Analytical Processing (SOLAP) is a powerful decision support systems tool for exploring the multidimensional perspective of spatial data. In recent years, remotely sensed data have been integrated into SOLAP cubes, and this improvement has advantages in spatio-temporal analysis for environment monitoring. However, the performance of aggregations in SOLAP still faces a considerab...

Spatial-OLAP (SOLAP) technologies are dedicated to multidimensional analysis of large volumes of (spatial) data. Spatial data are subject to different types of uncertainty, in particular spatial vagueness. Although several researches propose new models to cope with spatial vagueness, their integration in SOLAP systems is still in an embryonic state. Also, analyzing multidimensional data with me...

With the growing popularity of mobile computing and the empowerment of mobile devices by high end-users and decision-makers, the development of architectures based on web services for the deployment of mobile Spatial OLAP (SOLAP) applications is being perceived as a powerful solution. This paper deals with geospatial (web) Services-Oriented Architectures (SOA) for mobile processing of geo-decis...

Spatial OLAP (SOLAP) integrates spatial data into OLAP systems, and SOLAP models define spatial dimensions while measuring spatio-multidimensional operators. In this paper, the author presents the concepts of geographic and complex measures that allow integrating geographic and complex information as subjects of analysis in spatial data warehouses. The concept of geographic measure extends the ...

Integration of spatial data into multidimensional models leads to the concept of Spatial OLAP (SOLAP). Usually, SOLAP models exploit discrete spatial data. Few works integrate continuous field data into dimensions and measures. In this paper, we provide a multidimensional model that supports measures and dimension as continuous field data, independently of their implementation.