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A Multidimensional Model for Correct Aggregation of Geographic Measures

A Multidimensional Model for Correct Aggregation of Geographic Measures
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Author(s): Sandro Bimonte (Cemagref and UR TSCF, France), Marlène Villanova-Oliver (Laboratoire d’Informatique de Grenoble, France)and Jerome Gensel (Laboratoire d’Informatique de Grenoble, France)
Copyright: 2010
Pages: 22
Source title: Evolving Application Domains of Data Warehousing and Mining: Trends and Solutions
Source Author(s)/Editor(s): Pedro Nuno San-Banto Furtado (University of Coimbra, Portugal)
DOI: 10.4018/978-1-60566-816-1.ch008

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Abstract

Spatial OLAP refers to the integration of spatial data in multidimensional applications at physical, logical and conceptual levels. The multidimensional aggregation of geographic objects (geographic measures) exhibits theoretical and implementation problems. In this chapter, the authors present a panorama of aggregation issues in multidimensional, geostatistic, GIS and Spatial OLAP models. Then, they illustrate how overlapping geometries and dependency of spatial and alphanumeric aggregation are necessary for correctly aggregating geographic measures. Consequently, they present an extension of the logical multidimensional model GeoCube (Bimonte et al., 2006) to deal with these issues.

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