Abstract
In the last years, extending OLAP (On-Line Analytical Processing) systems with spatial and temporal features has attracted the attention of the GIS (Geographic Information Systems) and database communities. However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support. Further, the solutions proposed in the literature vary considerably in the kind of data that can be represented as well as the kind of queries that can be expressed. In this paper we present a conceptual framework for defining spatio-temporal data warehouses using an extensible data type system. We also define a taxonomy of different classes of queries of increasing expressive power, and show how to express such queries using an extension of the tuple relational calculus with aggregated functions.
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Vaisman, A., Zimányi, E. (2009). What Is Spatio-Temporal Data Warehousing?. In: Pedersen, T.B., Mohania, M.K., Tjoa, A.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2009. Lecture Notes in Computer Science, vol 5691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03730-6_2
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DOI: https://doi.org/10.1007/978-3-642-03730-6_2
Publisher Name: Springer, Berlin, Heidelberg
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