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Piet: a GIS-OLAP implementation

Published: 09 November 2007 Publication History

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.

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cover image ACM Conferences
DOLAP '07: Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
November 2007
112 pages
ISBN:9781595938275
DOI:10.1145/1317331
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 November 2007

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Author Tags

  1. GIS
  2. OLAP
  3. view materialization

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  • (2014)Modelling Spatial Decision Support Systems Focused on the Development of a Data WarehouseInternational Journal of Decision Support System Technology10.4018/ijdsst.20140701036:3(43-64)Online publication date: 1-Jul-2014
  • (2014)GeoBI Architecture Based on Free SoftwareGeographical Information Systems10.1201/b16871-10Online publication date: 27-May-2014
  • (2014)Parallel online spatial and temporal aggregations on multi-core CPUs and many-core GPUsInformation Systems10.1016/j.is.2014.01.00544(134-154)Online publication date: Aug-2014
  • (2014)A probabilistic data model and algebra for location-based data warehouses and their implementationGeoinformatica10.1007/s10707-013-0180-418:2(357-403)Online publication date: 1-Apr-2014
  • (2013)A State-of-the-Art in Spatio-Temporal Data Warehousing, OLAP and MiningData Mining10.4018/978-1-4666-2455-9.ch104(2021-2056)Online publication date: 2013
  • (2013)A Multidimensional Model for Correct Aggregation of Geographic MeasuresGeographic Information Systems10.4018/978-1-4666-2038-4.ch023(377-398)Online publication date: 2013
  • (2013)On Modeling and Analysis of Multidimensional Geographic DatabasesGeographic Information Systems10.4018/978-1-4666-2038-4.ch009(91-107)Online publication date: 2013
  • (2013)An automatic transition from geographic CIM to Spatial Data Warehouse2013 International Conference on Control, Decision and Information Technologies (CoDIT)10.1109/CoDIT.2013.6689562(306-311)Online publication date: May-2013
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  • (2012)High-performance online spatial and temporal aggregations on multi-core CPUs and many-core GPUsProceedings of the fifteenth international workshop on Data warehousing and OLAP10.1145/2390045.2390060(89-96)Online publication date: 2-Nov-2012
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