Abstract
The increased availability of spatial data in recent years has lead to new challenges in the analysis of large multidimensional datasets. One solution is to integrate GIS with OLAP and relational databases. Another strategy has been to leverage existing spatial capabilities of databases to perform spatial OLAP. In this article, we review existing modelling strategies for spatial data warehousing at all three levels: conceptual, logical and implementation. We gather the most essential requirements for handling spatial data and use insights from spatial databases and GIS systems to design a meta-framework that would enable a user-centric modelling of complex data. Our strategy is to keep the user as the focal point in the analysis process and lay the foundation for clear data abstraction at different levels using multidimensional abstract data types and operations and thus support complex spatial data in data warehouses.
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