Abstract
Investigation shows that a huge number of spatial data exists in current business databases. Traditional data warehousing and OLAP, however, could not exploit the spatial information to get deep insight into the business data in decision making. In this paper, we propose a novel approach to enabling spatial OLAP by aggregating on the spatial hierarchy. A spatial index mechanism is employed to derive the spatial hierarchy for pre-aggregation and materialization, which in turn are leveraged by the OLAP system to efficiently answer spatial OLAP queries. Our prototype system shows that the proposed approach could be integrated easily into the existing data warehouse and OLAP systems to support spatial analysis. Preliminary experiment results are also presented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baralis, E., Paraboschi, S., Teniente, E.: Materialized View Selection in a Multidimensional Database. In: Proceedings of VLDB Conference (1997)
Colossi, N., Malloy, W., Reinwald, B.: Relational extensions for OLAP. IBM SYSTEMS JOURNALÂ 41(4) (2002)
Adler, D.W.: DB2 Spatial Extender - Spatial data within the RDBMS. In: Proceedings of VLDB Conference, pp. 687–690 (2001)
Daratech: Geographic Information Systems Markets and Opportunities. Daratech, Inc. (2000)
Gray, J., Chaudhuri, S., Bosworth, A., et al.: Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals. Data Mining and Knowledge Discovery Journal 1, 29–53 (1997)
Gaede, V., Gnther, O.: Multidimensional Access Methods. ACM Computing Surveys (1997)
Gupta, H.: Selection of Views to Materialize in a Data Warehouse. In: Proceedings of International Conference on Database Theory (1997)
Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann Publisher, Inc., San Francisco (2001)
Han, J., Stefanovic, N., Koperski, K.: Selective Materialization: An Efficient Method for Spatial Data Cube Construction. In: Wu, X., Kotagiri, R., Korb, K.B. (eds.) PAKDD 1998. LNCS, vol. 1394. Springer, Heidelberg (1998)
Java OLAP Interface (JOLAP), version 0.85. Java Community Process (May 2002), Available at http://jcp.org/en/jsr/detail?id=069
Kothui, R.K.V., Ravada, S., Abugov, D.: Quadtree and R-tree Indexes in Oracle Spatial: A Comparison using GIS Data. In: ACM SIGMOD Conference (2002)
Papadias, D., Kalnis, P., Zhang, J., Tao, Y.: Efficient OLAP operations in spatial data warehouses. Technical Report HKUST-CS01-01 (January 2001)
Papadias, D., Tao, Y., Kalnis, P., Zhang, J.: Indexing Spatio-Temporal Data Warehouses. In: Proceedings of International Conference on Data Engineering (2002)
Stefanovic, N., Han, J., Koperski, K.: Object-Based Selective Materialization for Efficient Implementation of Spatial Data Cubes. TKDE 12(6), 938–958 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, L., Li, Y., Rao, F., Yu, X., Chen, Y., Liu, D. (2003). An Approach to Enabling Spatial OLAP by Aggregating on Spatial Hierarchy. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2003. Lecture Notes in Computer Science, vol 2737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45228-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-540-45228-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40807-9
Online ISBN: 978-3-540-45228-7
eBook Packages: Springer Book Archive