R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
On Data Warehouse and GIS Integration
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
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Current geographical information systems (GIS) handle large amounts of geographical data stored usually in relational databases. Database vendors developed special database plug-ins in order to make retrieval of geographical data more efficient. Basically, they implement spatial indexing techniques aimed at speeding-up spatial query processing. This approach is suitable for those spatial queries, which select objects in certain user-defined area. Similarly as on-line transaction processing (OLTP) systems evolved into on-line analytical processing (OLAP) systems for supporting more complicated analytical tasks, similar evolution can be expected in the context of geographical information analytical processing. This paper describes the GOLAP system consisting of a commercial OLAP system enriched with a spatial index. Experiments comparing efficiency of original OLAP and the extended one are presented.