Data warehouses are being considered as substantial elements for decision support systems. They are usually structured according to the multidimensional paradigm, i.e. datacubes. Spatial datacubes contain spatial components that allow spatial visualization and aggregation. One may need to use several spatial datacubes which may be semantically heterogeneous and having different degrees of appropriateness to the context of use. Interoperability has been considered as an appropriate paradigm for using several datacubes. However, the interoperability process may become more complex with increasing number of candidate datacubes. On the other hand, recommendation is a process that proposes personalized queries according to the user's needs. This paper proposes an approach that aims to enhance the interoperability process by selecting, among candidate datacubes, those that better fit the interoperability process.
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