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dc.contributor.authorESCRIBANO, Ariel-
dc.contributor.authorGOMEZ, Leticia-
dc.contributor.authorKUIJPERS, Bart-
dc.contributor.authorVAISMAN, Alejandro-
dc.identifier.citationPEDERSEN, Torben Bach & SONG, Il-Yeol (Ed.) Proceedings of the ACM 10th International Workshop on Data Warehousing and OLAP. p. 73-80.-
dc.description.abstractData aggregation in Geographic Information Systems (GIS) is a desirable feature, although only marginally present in commercial systems nowadays, mostly through ad-hoc solu- tions. Integration between GIS and OLAP systems is still needed in commercial systems. With this in mind, we have developed Piet, a system that that makes use of a novel query processing technique: first, a process called subpoly- gonization decomposes each thematic layer into open con- vex polygons; then, another process computes and stores in a database the overlay of those layers for later use by the query processor. We describe in detail the implementation of Piet, and provide evidence, through experimentation over real-world maps, that overlay precomputation for spatial ag- gregate queries can be competitive with GIS systems that employ indexing schemes based on R-trees. Given that the data model and implementation do not prevent the use of traditional indexing techniques as R-tree and aR-trees, we our proposal against these techniques in our experiments.-
dc.titlePiet: a GIS-OLAP Implementation-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsPEDERSEN, Torben Bach-
local.bibliographicCitation.authorsSONG, Il-Yeol-
local.bibliographicCitation.conferencenameACM International Workshop on Data Warehousing and OLAP-
local.type.specifiedProceedings Paper-
local.bibliographicCitation.btitleProceedings of the ACM 10th International Workshop on Data Warehousing and OLAP-
item.accessRightsOpen Access-
item.fullcitationESCRIBANO, Ariel; GOMEZ, Leticia; KUIJPERS, Bart & VAISMAN, Alejandro (2007) Piet: a GIS-OLAP Implementation. In: PEDERSEN, Torben Bach & SONG, Il-Yeol (Ed.) Proceedings of the ACM 10th International Workshop on Data Warehousing and OLAP. p. 73-80..-
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