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Integration of Geographic Information into Multidimensional Models
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Integration of Geographic Information into Multidimensional Models
Sandro Bimonte1 , Anne Tchounikine1 and Michela Bertolotto2 
| (1) |
LIRIS (Laboratoire d’InfoRmatique en Images et Systèmes d’information) UMR CNRS 5205, INSA, 7 avenue Capelle, 69621 Villeurbanne Cedex, France |
| (2) |
School of Computer Science and Informatics, University College, Dublin, Belfield, Dublin, 4, |
Abstract
Data warehousing and On Line Analytical Processing (OLAP) are technologies intended to support business intelligence. Spatial
OLAP integrates spatial data into OLAP systems. Spatial OLAP models reformulate main OLAP concepts to define spatial dimensions
and measures, and spatio-multidimensional navigation operators. Spatial OLAP reduces geographic information to its spatial
component without taking into account map generalization relationships into the multidimensional decision process. In this
paper, we present the concept of Geographic Dimension which extends the classical definition of spatial dimension by introducing map generalization hierarchies, as they enhance
analysis capabilities of SOLAP models and systems. A Geographic Dimension is described by spatial, descriptive and/ormap generalization hierarchies. These hierarchies permit to define ad-hoc aggregation functions, but at the same time raise several modeling
problems.
Keywords Spatial OLAP - Multidimensional Models - Map Generalization - Geographic Information
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