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Efficient Storage and Management of Environmental Information

Spatial Data warehouses pose many challenging requirements with respect to the design of the data model due to the nature of analytical operations and the nature of the views to be maintained by the spatial warehouse. The first challenge is due to the multi-dimensional nature of each dimension itself. In a traditional data warehouse the various dimensions contributing to the warehouse data are simple in nature, each having different attributes. Data models such as the star schema, fact constellation schema, snowflake schema or the multi-dimensional model, can therefore, be used to represent the traditional data warehouse. On the other hand, the different dimensions in a spatial data warehouse comprise of different types of data, each of which is multi-dimensional in nature. The current available data models are not adequate for such domains. In this paper, we propose a data model that is well suited for such domains, called the cascaded star model that is capable of representing multiple dimensions of a spatial data warehouse, where each dimension is multi-dimensional. The nature of the queries in such domains is different from that of traditional data warehouses (such as fly-by of a region), and therefore we propose a suitable architecture that allows specification of the queries and their visual presentation.