Issue No. 11 - Nov. (2013 vol. 19)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2013.93
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.
Visualization, Genetic algorithms, Three-dimensional displays, Data visualization, Genetics, Sociology, Statistics
S. Lafon, F. Bouali, C. Guinot and G. Venturini, "Hierarchical Reorganization of Dimensions in OLAP Visualizations," in IEEE Transactions on Visualization & Computer Graphics, vol. 19, no. 11, pp. 1833-1845, 2013.