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Hierarchical Reorganization of Dimensions in OLAP Visualizations
Nov. 2013 (vol. 19 no. 11)
pp. 1833-1845
S. Lafon, Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
F. Bouali, Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
C. Guinot, Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
G. Venturini, Comput. Sci. Lab., Univ. Francois-Rabelais of Tours, Tours, France
In this paper, we propose a new method for the visual reorganization of online analytical processing (OLAP) cubes that aims at improving their visualization. Our method addresses dimensions with hierarchically organized members. It uses a genetic algorithm that reorganizes k-ary trees. Genetic operators perform permutations of subtrees to optimize a visual homogeneity function. We propose several ways to reorganize an OLAP cube depending on which set of members is selected for the reorganization: all of the members, only the displayed members, or the members at a given level (level by level approach). The results that are evaluated by using optimization criteria show that our algorithm has a reliable performance even when it is limited to 1 minute runs. Our algorithm was integrated in an interactive 3D interface for OLAP. A user study was conducted to evaluate our approach with users. The results highlight the usefulness of reorganization in two OLAP tasks.
Index Terms:
Visualization,Genetic algorithms,Three-dimensional displays,Data visualization,Genetics,Sociology,Statistics,interactive knowledge discovery,Dimension reorganization,visual OLAP
Citation:
S. Lafon, F. Bouali, C. Guinot, G. Venturini, "Hierarchical Reorganization of Dimensions in OLAP Visualizations," IEEE Transactions on Visualization and Computer Graphics, vol. 19, no. 11, pp. 1833-1845, Nov. 2013, doi:10.1109/TVCG.2013.93
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