Enriching Spatial OLAP with Map Generalization: a Conceptual Multidimensional Model

Abstract

Map generalization is used to derive maps for secondary scales and/or specific goals. This operation greatly benefits spatial decision support systems as it can provide a global and simplified representation of a phenomenon discarding irrelevant information. The recent popularity of OLAP systems for various application domains has generated much interest for the development of spatial OLAP (SOLAP) models that integrate spatial data in data warehouse and OLAP systems. Although powerful under some respect, current SOLAP models cannot support map generalization capabilities. In this paper, we present a conceptual multidimensional model integrating map generalization. The model extends SOLAP spatial hierarchies introducing multi-association relationships, and supports imprecise measures.