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Piet: a GIS-OLAP implementation
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Data Warehousing and OLAP archive
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP table of contents
Lisbon, Portugal
SESSION: Spatio-temporal data warehouses and data mining table of contents
Pages: 73-80  
Year of Publication: 2007
ISBN:978-1-59593-827-5
Authors
Ariel Escribano  Universidad de Buenos Aires, Buenos Aires, Argentina
Leticia Gomez  Instituto Tecnologico de Buenos Aires, Buenos Aires, Argentina
Bart Kuijpers  University of Hasselt, Hasselt, Belgium
Alejandro A. Vaisman  Universidad de Buenos Aires, Buenos Aires, Argentina
Sponsors
ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

Data aggregation in Geographic Information Systems (GIS) is a desirable feature, although only marginally present in commercial systems, which also fail to provide integration between GIS and OLAP (On Line Analytical Processing). With this in mind, we have developed Piet, a system that makes use of a novel query processing technique: first, a process called sub-polygonization decomposes each thematic layer in a GIS, into open convex polygons; then, another process computes and stores in a database the overlay of those layers for later use by a query processor. We describe the implementation of Piet, and provide experimental evidence that overlay precomputation can outperform GIS systems that employ indexing schemes based on R-trees.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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S. Haesevoets, B. Kuijpers, and A. Vaisman. Spatial aggregation: Data model and implementation. In Submitted for revew, 2007.
 
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Collaborative Colleagues:
Ariel Escribano: colleagues
Leticia Gomez: colleagues
Bart Kuijpers: colleagues
Alejandro A. Vaisman: colleagues