On aggregation issues in spatial data management

  • Authors:

  • M. Indulska;M. E. Orlowska

  • Affiliations:

  • The University of Queensland, Brisbane, Australia;The University of Queensland, Brisbane, Australia

  • Venue:
  • ADC '02 Proceedings of the 13th Australasian database conference - Volume 5
  • Year:
  • 2002

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Abstract

Large amounts of information can be overwhelming and costly process, especially when transmitting data over a network. A typical modern Geographical Information System (GIS) brings all types of data together based on the geographic component of the data and provides simple point-and-click query capabilities well as complex analysis tools. Querying a Geographical Information System, however, can be prohibitively expensive due to the large amounts of data which may need to be processed. Since the use of GIS technology has grown dramatically in the past few years, there is now a need more than ever, to provide users with the fastest and least expensive query capabilities, especially since an approximated 80% of data stored in corporate databases has a geographical component. However, not every application requires the same, high quality data for its processing. In this paper we address the issues of reducing the cost and response time of GIS queries by pre-aggregating data by compromising the data accuracy and precision. We present computational issues in generation of multi-level resolutions of spatial data and show that the problem of finding the best approximation for the given region and a real value function on this region, under a predictable error, in general is NP-complete.