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Spatial data cubes based on shared dimensions and neighbourhood relationship concepts

Author

Listed:
  • Tarik De Melo e Silva Rocha
  • Rodrigo Rocha Silva
  • Tiago Garcia De Senna Carneiro
  • Joubert De Castro Lima

Abstract

A data cube has exponential storage and runtime complexities with linearly increasing dimensionality; in addition, a spatial data cube further complicates the issue since it integrates spatial features into a data cube. In this paper, a new data cube approach, named spatial cubing, or simply S-cubing, implements two spatial indexing techniques and two spatial non-relational representations. S-cubing based on shared dimensions is the first non-relational solution designed to support spatial data cubes with continuous dimensions, resolution hierarchies and multiple spatial measures and is capable of running on multi-core computer architectures. S-cubing, based on neighbourhood relationships, implements a new data cube hierarchy algorithm using relationships among cells of a regular grid. Thus, this algorithm creates thematic maps from non-geopolitical regular areas, therein avoiding manual hierarchy definitions. A sequential version is found to be faster than a PostGIS implementation and the parallel version achieved a speedup of 13 with 24 threads.

Suggested Citation

  • Tarik De Melo e Silva Rocha & Rodrigo Rocha Silva & Tiago Garcia De Senna Carneiro & Joubert De Castro Lima, 2021. "Spatial data cubes based on shared dimensions and neighbourhood relationship concepts," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 37(3), pages 308-335.
    • Handle: RePEc:ids:ijbisy:v:37:y:2021:i:3:p:308-335
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