Résumé. Les entrepôts de données spatiales et les systèmes Spatial OLAP sont des technologies d’aide à la décision permettant l’analyse en ligne des gros jeux de données géo-référencées. Dans un tel type de systèmes, la qualité de l’analyse dépend : de la qualité des données entreposées, de comment les agrégations sont effectuées, et de comment les données entreposées sont explorées. Dans cet a...

In recent years, applications aimed at exploring and analyzing spatial data have emerged, powered by the increasing need of software that integrates Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP). These applications have been called SOLAP (Spatial OLAP). In previous work, the authors have introduced Piet, a system based on a formal data model that integrates in a ...

The need for effective spatial knowledge discovery in risk assessment increases as the amount of the spatial data which is handled and analyzed for risk assessment has enlarged. Such large variety of spatial data should be integrated from multiple sources presenting different types, semantics, and level of details weather geometrically, temporally, or thematically. Therefore, spatial knowledge ...

Metadata should help users to assess the quality (fitness for use) of geospatial data, thus reducing the risk of data misuse. However, metadata presents limitations and remain largely unused. There still exists a need to provide information to users about data quality in a more meaningful way. This research aims to dynamically communicate quality information to the users in a rapid and intuitiv...