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 evolutions into account. Hence, a dilemma appears for the designer of data warehouses:
either keeping trace of evolutions therefore limiting the capability of comparison for analysts, or mapping all data in a given version of the structure that entails alteration (or even loss) of data. We propose a novel approach that offers another alternative, allowing to track history but also to compare data, mapped into static structures. We define a conceptual model and provide possible logical adaptations to implement it on current commercial OLAP systems. At last, we present the global architecture that we used for our prototype.