Visualization Symposium, IEEE Pacific (2012)
Songdo, Korea (South)
Feb. 28, 2012 to Mar. 2, 2012
Rene Rosenbaum , Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, 95616-8562, U.S.A.
Jian Zhi , Department of Industrial Engineering and Operations Research, Columbia University, NY 10027, U.S.A.
Bernd Hamann , Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, 95616-8562, U.S.A.
Progressive refinement is a methodology that makes it possible to elegantly integrate scalable data compression, access, and presentation into one approach. Specifically, this paper concerns the effective use of progressive parallel coordinates (PPCs), utilized routinely for high-dimensional data visualization. It discusses how the power of the typical stages of progressive data visualization can also be utilized fully for PPCs. Further, different implementations of the underlying methods and potential application domains are described. The paper also presents empirical results concerning the benefits of PPC with regard to efficient data management and improved presentation, indicating that the proposed approach is able to close the gap between data handling and visualization.
J. Zhi, R. Rosenbaum and B. Hamann, "Progressive parallel coordinates," Visualization Symposium, IEEE Pacific(PACIFICVIS), Songdo, Korea (South), 2012, pp. 25-32.