Anne Tchounikine

Learn More
When changes occur on data organization, conventional multidimensional structures are not adapted because dimensions are supposed to be static. In many cases, especially when time covered by the data warehouse is large, dimensions of the hypercube must be redesigned in order to integrate evolutions. We propose an approach allowing to track history but also(More)
Building multidimensional systems requires gathering data from heterogeneous sources throughout time. Then, data is integrated in multidimensional structures organized around several axes of analysis, or dimensions. But these analysis structures are likely to vary over time and the existing multidimensional models do not (or only partially) take these(More)
Data warehouses and OLAP systems help to interactively analyze huge volumes of data. Spatial OLAP refers to the integration of spatial data in multidimensional applications at the physical, logical and conceptual level. In order to include spatial information as a result of the decision-making process, we propose to define spatial measures as geographical(More)