Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/7899
Title: | A Data Model for Moving Objects Supporting Aggregation | Authors: | KUIJPERS, Bart VAISMAN, Alejandro |
Issue Date: | 2007 | Publisher: | IEEE Press | Source: | KUIJPERS, Bart & NANNI, Miro (Ed.) Proceedings of the ICDE Workshop on Spatio-Temporal Data Mining (STDM'07). | Abstract: | Moving objects databases (MOD) have been receiving increasing attention from the database community in re- cent years, mainly due to the wide variety of applications that technology allows nowadays. Trajectories of moving objects like cars or pedestrians, can be reconstructed by means of samples describing the locations of these objects at certain points in time. Although there are many propos- als for modeling and querying moving objects, only a small part of them address the problem of aggregation of moving objects data in a GIS (Geographic Information Systems) scenario. In previous work we presented a formal model where the geometric components of the thematic layers in a GIS are represented as an OLAP (On Line Analytical Pro- cessing) dimension hierarchy, and introduced the notion of spatial aggregation. In this paper we extend this proposal in order to address moving object aggregation over a GIS. In this way, complex aggregate queries can be expressed in an elegant fashion. We present the data model, characterize the kinds of queries that may appear in this scenario, and show how these queries can be expressed as an aggrega- tion over the result given by a first order formula expressing constraints over the geometries of the layers. databases. | Keywords: | OLAP, Moving Objects | Document URI: | http://hdl.handle.net/1942/7899 | DOI: | 10.1109/ICDEW.2007.4401040 | Category: | C2 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
07-STDM.pdf | 271.99 kB | Adobe PDF | View/Open |
SCOPUSTM
Citations
6
checked on Sep 3, 2020
WEB OF SCIENCETM
Citations
5
checked on Mar 23, 2024
Page view(s)
70
checked on Nov 7, 2023
Download(s)
258
checked on Nov 7, 2023
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.