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Article: Indexing and Retrieval of Historical Aggregate Information about Moving Objects

TitleIndexing and Retrieval of Historical Aggregate Information about Moving Objects
Authors
Issue Date2002
PublisherIEEE, Computer Society.
Citation
Bulletin of the Technical Committee on Data Engineering, 2002, v. 25 n. 2, p. 10-17 How to Cite?
AbstractSpatio-temporal databases store information about the positions of individual objects over time. In many applications however, such as traffic supervision or mobile communication systems, only summarized data, like the average number of cars in an area for a specific period, or phones serviced by a cell each day, is required. Although this information can be obtained from operational databases, its computation is expensive, rendering online processing inapplicable. A vital solution is the construction of a spatiotemporal data warehouse. In this paper, we describe a framework for supporting OLAP operations over spatiotemporal data. We argue that the spatial and temporal dimensions should be modeled as a combined dimension on the data cube and present data structures, which integrate spatiotemporal indexing with pre-aggregation. While the well-known materialization techniques require a-priori knowledge of the grouping hierarchy, we develop methods that utilize the proposed structures for efficient execution of ad-hoc group-bys. Our techniques can be used for both static and dynamic dimensions.
Persistent Identifierhttp://hdl.handle.net/10722/47095

 

DC FieldValueLanguage
dc.contributor.authorPapadias, Den_HK
dc.contributor.authorTao, Yen_HK
dc.contributor.authorZhang, Jen_HK
dc.contributor.authorMamoulis, Nen_HK
dc.contributor.authorShen, Qen_HK
dc.contributor.authorSun, Jen_HK
dc.date.accessioned2007-10-30T07:07:01Z-
dc.date.available2007-10-30T07:07:01Z-
dc.date.issued2002en_HK
dc.identifier.citationBulletin of the Technical Committee on Data Engineering, 2002, v. 25 n. 2, p. 10-17en_HK
dc.identifier.urihttp://hdl.handle.net/10722/47095-
dc.description.abstractSpatio-temporal databases store information about the positions of individual objects over time. In many applications however, such as traffic supervision or mobile communication systems, only summarized data, like the average number of cars in an area for a specific period, or phones serviced by a cell each day, is required. Although this information can be obtained from operational databases, its computation is expensive, rendering online processing inapplicable. A vital solution is the construction of a spatiotemporal data warehouse. In this paper, we describe a framework for supporting OLAP operations over spatiotemporal data. We argue that the spatial and temporal dimensions should be modeled as a combined dimension on the data cube and present data structures, which integrate spatiotemporal indexing with pre-aggregation. While the well-known materialization techniques require a-priori knowledge of the grouping hierarchy, we develop methods that utilize the proposed structures for efficient execution of ad-hoc group-bys. Our techniques can be used for both static and dynamic dimensions.en_HK
dc.format.extent123703 bytes-
dc.format.extent4295 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE, Computer Society.en_HK
dc.rights©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleIndexing and Retrieval of Historical Aggregate Information about Moving Objectsen_HK
dc.typeArticleen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.hkuros71426-
dc.identifier.hkuros81201-

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