The Approach for Data Warehouse to Answering Spatial OLAP Queries
Spatial data are pervasive in traditional business applications like the customer address and store location. With the advance in mobile computing and digital earth, much more spatial data have been collected, stored and integrated into the business system. Analyzing these spatial data, to understand the relationships among them, and the relationships between spatial data and non-spatial data, would help companies gain deeper geographical insight into their business and customers, and explore more other potential business value. However, neither the design of data warehouse takes the spatial dimension of data into consideration, nor the data warehousing tools (e.g., ETL) support spatial data in the preprocessing stages. Consequently, the deployed data warehouses without spatial aware can not support spatial analysis. Research in spatial data warehousing and OLAP is an necessary to exploit the information and knowledge hidden in the spatial dimension and spatial relationships during the processing of data warehousing. This paper proposes a novel approach for data warehouses to be spatially aware and to provide certain spatial analysis capabilities. A spatial transformation builder is developed and deployed as an ETL tool to extract facts including complex spatial relationships from spatial data sources according to business requirements. The facts capturing the spatial relationships from original sources are presented by non-spatial relation model and stored in the data warehouse, where some kinds of spatial OLAP queries could be issued.
KeywordsSpatial Data Spatial Relationship Data Warehouse Spatial Object Star Schema
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- 1.Fu, L., Hammer, J.: CubiST: A New Algorithm for Improving the Performance of Ad-hoc OLAP Queries. In: Proceedings of the ACM Third International Workshop on Data Warehousing and OLAP, Washington, DC (2002)Google Scholar
- 2.OMG: Common Warehouse Metamodel Specification Version 1.0.2. (2001), http://www.omg.org
- 3.Daratech: Geographic Information Systems Markets and Opportunities. Daratech, Inc (2000)Google Scholar
- 5.Rauber, A., Tomich, P., Riedel, H.: Integrating Geo-spatial Data into OLAP Systems using a Set-based Quad-tree Representation. In: Proceedings of the 4th IEEE / IFIP International Conference on Information Technology for BALANCED AUTOMATION SYSTEMS in Production and Transportation (BASYS2000). Kluwer Academic Publishers, Berlin (2000)Google Scholar
- 6.Pedersen, T.B., Tryfona, N.: Pre-aggregation in Spatial Data Warehouses. In: Proceedings of the Seventh International Symposium on Spatial and Temporal Databases, Redondo Beach, California, USA, pp. 460–478 (2001)Google Scholar