Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Spatiotemporal Data Warehouses

  • Yufei TaoEmail author
  • Dimitris Papadias
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_362


Spatio-temporal online analytical processing; Spatio-Temporal OLAP


Consider Nregions R1, R2,…,RN and a time axis consisting of discrete timestamps 1, 2,…,T, where T represents the total number of recorded timestamps (i.e., the length of history). The position and area of a region Ri may vary along with time, and its extent at timestamp t is denoted as Ri (t). Each region carries a set of measures Ri (t).ms, also called the aggregate data of Ri (t). The measures of regions change asynchronously with their extents. In other words, the measure of Ri (1 ≤ iN) may change at a timestamp t (i.e., Ri (t).msRi (t − 1).ms), while its extent remains the same (i.e., \( {R}_i(t) = {R}_i\left(t-1\right) \)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Chinese University of Hong KongHong KongChina
  2. 2.Department of Computer Science and EngineeringHong Kong University of Science and TechnologyKowloonHong Kong

Section editors and affiliations

  • Dimitris Papadias
    • 1
  1. 1.Dept. of Computer Science and Eng.Hong Kong Univ. of Science and TechnologyKowloonHong Kong