Using R-Trees for Interactive Visualization of Large Multidimensional Datasets

Large, multidimensional datasets are difficult to visualize and analyze. Visualization interfaces are constrained in resolution and dimension, so cluttering and problems of projecting many dimensions into the available low dimensions are inherent. Methods of real-time interaction facilitate analysis, but often these are not available due to the computational complexity required to use them. By organizing the dataset into a level-of-detail (LOD) hierarchy, our proposed method solves problems of both inefficient interaction and visual cluttering. We do this by introducing an implementation of R-trees for large multidimensional datasets. We introduce several useful methods for interaction, by queries and refinement, to explain the relevance of interaction and show that it can be done efficiently with R-trees. In order to project many dimensions into lower-dimensional spaces used for visualization, we utilize properties of the R-tree as well as existing methods for multidimensional visual...

• Type: Journal
• Year: 2010
• Where: ISVC
• Authors: Alfredo Giménez, René Rosenbaum, Mario Hlawitschka, Bernd Hamann
• Keywords: Applied Computing, Dimensions, ISVC 2010, Large Multidimensional Datasets, Multidimensional Datasets