Worlds within worlds: metaphors for exploring n-dimensional virtual worlds
UIST '90 Proceedings of the 3rd annual ACM SIGGRAPH symposium on User interface software and technology
Designing glyphs to exploit patterns in multidimensional datasets
CHI '95 Conference Companion on Human Factors in Computing Systems
Visual exploration of large data sets
Communications of the ACM
Designing Pixel-Oriented Visualization Techniques: Theory and Applications
IEEE Transactions on Visualization and Computer Graphics
Visualization Techniques for Mining Large Databases: A Comparison
IEEE Transactions on Knowledge and Data Engineering
Similarity Clustering of Dimensions for an Enhanced Visualization of Multidimensional Data
INFOVIS '98 Proceedings of the 1998 IEEE Symposium on Information Visualization
Query, analysis, and visualization of hierarchically structured data using Polaris
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Exploring N-dimensional databases
VIS '90 Proceedings of the 1st conference on Visualization '90
XmdvTool: integrating multiple methods for visualizing multivariate data
VIS '94 Proceedings of the conference on Visualization '94
Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
Explaining optimization in genetic algorithms with uniform crossover
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
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The combination of pixelization and dimensional stacking yields a highly informative visualization that uniquely facilitates feature discovery and exploratory analysis of multidimensional, multivariate data. Pixelization is the mapping of each data point in some set to a pixel in an image. Dimensional stacking is a layout method where N dimensions are projected into 2. We have combined both methods to support visual data mining of a vast neuroscience database. Images produced from this approach have now appeared in the Journal of Neurophysiology [1] and are being used for educational purposes in neuroscience classes at Emory University. In this paper we present our combination of dimensional stacking and pixelization, our extensions to these methods, and how our techniques have been used in neuroscience investigations.