Multi-dimensional analysis is one of the most important applications of data warehouses, giving the possibility to aggregate and compare data along dimensions relevant in the application domain. Typically time is one of the dimensions we nd in data warehouses allowing comparisons of di erent periods. The instances of dimensions, however, change over time - countries unite and separate, products emerge and vanish, organizational structures evolve. In current data warehouse technology these changes cannot be represented adequately since all dimensions are (implicitly) considered as orthogonal, putting heavy restrictions on the validity of OLAP queries spanning several periods. We propose an extension of the multi-dimensional data model employed in data warehouses allowing to cope correctly with changes in dimension data: a temporal multi-dimensional data model allows the registration of temporal versions of dimension data. Mappings are provided to transfer data between di erent temporal versions and enable the system to correctly answer queries spanning multiple periods and thus di erent versions of dimension data.

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