An Architecture for Dimensional and Spatial Analyses Integration

During the last 30 years, decisions involving conventional data have been supported by traditional decision support systems, like EIS (Executive Information Systems), DSS (Decision Support Systems) and lately OLAP (On-Line Analytical Processing) systems on Data Warehouse (DW) environments. Another kind of system also used by decision makers is Geographical Information System (GIS). These systems focus on spatial analysis and are more commonly used in specific application domains like Cartography, Insurance, Health and Environment Management. In this paper, we propose an architecture that supports dimensional and spatial analyses, which takes advantage of the main features and functionalities of OLAP and GIS tools, through an integration model at conceptual/logical level. A case study is described which applies the proposed framework. 1