|Title||Using R-Trees for Interactive Visualization of Large Multidimensional Datasets
|in||Proceedings of the 6th International Symposium on Visual Computing|
Alfredo Giménez, Rene Rosenbaum, Mario Hlawitschka, Bernd Hamann |
|Location||Las Vegas, NV|
|Date||November 29-December 1, 2010|
Large, multidimensional datasets are difficult to visualize and interact with in real time. Visualization interfaces are constrained in resolution and dimension, so cluttering and problems of projecting many dimensions into the available low dimensions are inherent. By organizing the dataset into a level of detail (LOD) hierarchy, our proposed method solves problems of inefficient interaction and 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. 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 visualization. We examine the applicability of hierarchical parallel coordinates to datasets organized within an R-tree, and build upon previous work in hierarchical star coordinates to introduce a novel method for visualizing bounding hyperboxes of internal R-tree nodes. Finally, we examine two datasets using our proposed method and present and discuss results.