Interactive Hierarchical Dimension Ordering, Spacing and Filtering for Exploration of High Dimensional Datasets

Large numbers of dimensions not only cause clutter in multidimensional visualizations, but also make it difficult for users to navigate the data space. Effective dimension management, such as dimension ordering, spacing and filtering, is critical for visual exploration of such datasets. Dimension ordering and spacing explicitly reveal dimension relationships in arrangement-sensitive multidimensional visualization techniques, such as Parallel Coordinates, Star Glyphs, and Pixel-Oriented techniques. They facilitate the visual discovery of patterns within the data. Dimension filtering hides some of the dimensions to reduce clutter while preserving the major information of the dataset. In this paper, we propose an interactive hierarchical dimension ordering, spacing and filtering approach, called DOSFA. DOSFA is based on dimension hierarchies derived from similarities among dimensions. It is a scalable multi-resolution approach making dimensional management a tractable task. On the on...

• Type: Conference
• Year: 2003
• Where: INFOVIS
• Authors: Jing Yang, Wei Peng, Matthew O. Ward, Elke A. Rundensteiner
• Keywords: Dimension Management, Dimension Ordering, Dimensions, INFOVIS 2003