A State-of-the-Art in Spatio-Temporal Data Warehousing, OLAP and Mining

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Author(s): Leticia Gómez (Instituto Tecnológico de Buenos Aires, Argentina), Bart Kuijpers (Hasselt University and Transnational University of Limburg, Belgium), Bart Moelans (Hasselt University and Transnational University of Limburg, Belgium)and Alejandro Vaisman (Universidad de la Republica, Uruguay)
Copyright: 2011
Pages: 37
Source title: Integrations of Data Warehousing, Data Mining and Database Technologies: Innovative Approaches
Source Author(s)/Editor(s): David Taniar (Monash University, Australia)and Li Chen (LaTrobe University, Australia)
DOI: 10.4018/978-1-60960-537-7.ch009

Keywords: Data Mining / Data Mining and Databases / Information Science Reference / Library & Information Science

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Abstract

Geographic Information Systems (GIS) have been extensively used in various application domains, ranging from economical, ecological and demographic analysis, to city and route planning. Nowadays, organizations need sophisticated GIS-based Decision Support System (DSS) to analyze their data with respect to geographic information, represented not only as attribute data, but also in maps. Thus, vendors are increasingly integrating their products, leading to the concept of SOLAP (Spatial OLAP). Also, in the last years, and motivated by the explosive growth in the use of PDA devices, the field of moving object data has been receiving attention from the GIS community, although not much work has been done to provide moving object databases with OLAP capabilities. In the first part of this paper we survey the SOLAP literature. We then address the problem of trajectory analysis, and review recent efforts regarding trajectory data warehousing and mining. We also provide an in-depth comparative study between two proposals: the GeoPKDD project (that makes use of the Hermes system), and Piet, a proposal for SOLAP and moving objects, developed at the University of Buenos Aires, Argentina. Finally, we discuss future directions in the field, including SOLAP analysis over raster data.

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A State-of-the-Art in Spatio-Temporal Data Warehousing, OLAP and Mining

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