Spatial data cubes based on shared dimensions and neighbourhood relationship concepts

Tarik De Melo e Silva Rocha, Rodrigo Rocha Silva, Tiago Garcia De Senna Carneiro and Joubert De Castro Lima

International Journal of Business Information Systems, 2021, vol. 37, issue 3, 308-335

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.

Keywords: spatial OLAP; multidimensional analysis; neighbourhood relationship; data cube; spatial measures; spatial indexing; continuous dimensions. (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbisy:v:37:y:2021:i:3:p:308-335

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