Piet: A GIS-OLAP implementation

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...

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Guardado en:
Detalles Bibliográficos
Publicado: 2007
Materias:
GIS
OLAP
view materialization
Commercial systems
Convex polygon
Data aggregation
Experimental evidence
Indexing scheme
On-line analytical processing
Pre-computation
Query processing techniques
Query processor
R-trees
Thematic layers
Data warehouses
Decision trees
Geographic information systems
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97815959_v_n_p73_Escribano
http://hdl.handle.net/20.500.12110/paper_97815959_v_n_p73_Escribano
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_97815959_v_n_p73_Escribano
record_format dspace
spelling paper:paper_97815959_v_n_p73_Escribano2023-06-08T16:38:07Z Piet: A GIS-OLAP implementation GIS OLAP view materialization Commercial systems Convex polygon Data aggregation Experimental evidence Indexing scheme OLAP On-line analytical processing Pre-computation Query processing techniques Query processor R-trees Thematic layers view materialization Data warehouses Decision trees Geographic information systems 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. © 2007 ACM. 2007 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97815959_v_n_p73_Escribano http://hdl.handle.net/20.500.12110/paper_97815959_v_n_p73_Escribano
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic GIS
OLAP
view materialization
Commercial systems
Convex polygon
Data aggregation
Experimental evidence
Indexing scheme
OLAP
On-line analytical processing
Pre-computation
Query processing techniques
Query processor
R-trees
Thematic layers
view materialization
Data warehouses
Decision trees
Geographic information systems
spellingShingle GIS
OLAP
view materialization
Commercial systems
Convex polygon
Data aggregation
Experimental evidence
Indexing scheme
OLAP
On-line analytical processing
Pre-computation
Query processing techniques
Query processor
R-trees
Thematic layers
view materialization
Data warehouses
Decision trees
Geographic information systems
Piet: A GIS-OLAP implementation
topic_facet GIS
OLAP
view materialization
Commercial systems
Convex polygon
Data aggregation
Experimental evidence
Indexing scheme
OLAP
On-line analytical processing
Pre-computation
Query processing techniques
Query processor
R-trees
Thematic layers
view materialization
Data warehouses
Decision trees
Geographic information systems
description 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. © 2007 ACM.
title Piet: A GIS-OLAP implementation
title_short Piet: A GIS-OLAP implementation
title_full Piet: A GIS-OLAP implementation
title_fullStr Piet: A GIS-OLAP implementation
title_full_unstemmed Piet: A GIS-OLAP implementation
title_sort piet: a gis-olap implementation
publishDate 2007
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97815959_v_n_p73_Escribano
http://hdl.handle.net/20.500.12110/paper_97815959_v_n_p73_Escribano
_version_ 1768545212551921664

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