Spatiotemporal aggregate computation: A survey

Inés Fernando Vega López, Richard Thomas Snodgrass, Bongki Moon

Research output: Contribution to journalArticle

101 Scopus citations

Abstract

Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and spatiotemporal data. We also present a model that reduces the evaluation of aggregate queries to the problem of selecting qualifying tuples and the grouping of these tuples into collections on which an aggregate function is to be applied. This model give us a framework that allows us to analyze and compare the different existing techniques for the evaluation of aggregate queries. At the same time, it allows us to identify opportunities for research on types of aggregate queries that have not been studied.

Original languageEnglish (US)
Pages (from-to)271-286
Number of pages16
JournalIEEE Transactions on Knowledge and Data Engineering
Volume17
Issue number2
DOIs
Publication statusPublished - Feb 2005

Keywords

  • Aggregate function
  • Aggregation queries
  • Spatiotemporal databases

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Information Systems

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