OLAP Formulations for Supporting Complex Spatial Objects in Data Warehouses

In recent years, there has been a large increase in the amount of spatial data obtained from remote sensing, GPS receivers, communication terminals and other domains. Data warehouses help in modeling and mining large amounts of data from heterogeneous sources over an extended period of time. However incorporating spatial data into data warehouses leads to several challenges in data modeling, management and the mining of spatial information. New multidimensional data types for spatial application objects require new OLAP formulations to support query and analysis operations on them. In this paper, we introduce a set of constructs called C3 for defining data cubes. These include categorization, containment and cubing operations, which present a fundamentally new, user-centric strategy for the conceptual modeling of data cubes. We also present a novel region-hierarchy concept that builds spatially ordered sets of polygon objects and employs them as first class citizens in the data cube....

• Type: Journal
• Year: 2011
• Where: DAWAK
• Authors: Ganesh Viswanathan, Markus Schneider
• Keywords: Data Warehouses, DAWAK 2011, Information Technology, Olap Cubes, Polygon Objects