Title: Exploring N-Dimensional Databases

Author(s): Jeff LeBlanc and Matthew O. Ward, Computer Science Department, and Norman Wittels, Electrical Engineering Department, Worcester Polytechnic Institute, Worcester, MA 01609

Source: Proc. of First IEEE Conference on Visualization (Visualization '90), 1990.

Abstract: The ability of researchers to generate or acquire data far outstrips their ability to analyze it. This problem is even more pronounced when the data is of high (greater than 4) dimensions. Visualization has been identified as a critical technique for exploring data sets, but the visualization tools developed to date have mostly concentrated on the display of low dimensioned data. Ideally a tool for examining N-dimensional data should allow the presentation of the data in a way that can be intuitively interpreted and allow the display of arbitrary views and subsets of the data. The work presented in this paper describes the creation of such a tool using a technique which we term dimensional stacking.

Matthew O. Ward (matt@cs.wpi.edu)