Data Exploration Combining Kinetic and Static Visualization Displays

We describe interactions between kinetic (moving) and static information displays. We have implemented "moxel" kinetic displays in a classic discovery platform with many standard information visualization and analytic tools, and experimented with interactions between them. Moxels, which generalize pixels, are an advanced, moving, form of iconographic display of the kind first developed in static form by Pickett and White (1966). As with the static graphic icons of those early displays, moxels provide a way of mapping together in one image multiple data variables, but with potentially more potency with in-place motion. We show examples of how the two kinds of displays have been integrated, and discuss issues with the integration of dynamic and static visualizations in a single environment. We discuss several interaction paradigms between them including linked brushing, multiple selections, and operations on selected regions

[1]  S. Smith,et al.  An Auditory Display for Exploratory Visualization of Multidimensional Data , 1989, Workstations for Experiments.

[2]  R. M. Pickett,et al.  Integrated displays of multiparameter and multimodality images , 1990, [1990] Proceedings of the First Conference on Visualization in Biomedical Computing.

[3]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[4]  R. Daniel Bergeron,et al.  Stereophonic and surface sound generation for exploratory data analysis , 1990, CHI '90.

[5]  Chris North,et al.  A Taxonomy of Multiple Window Coordinations , 1998 .

[6]  Georges G. Grinstein,et al.  Exvis: an exploratory visualization environment , 1989 .

[7]  Ronald M. Pickett,et al.  Evaluation of visualization systems , 2001 .

[8]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[9]  Georges G. Grinstein,et al.  Iconographic Displays For Visualizing Multidimensional Data , 1988, Proceedings of the 1988 IEEE International Conference on Systems, Man, and Cybernetics.

[10]  K. Marx,et al.  Applications of Machine Learning and High‐Dimensional Visualization in Cancer Detection, Diagnosis, and Management , 2004, Annals of the New York Academy of Sciences.

[11]  Georges Grinstein,et al.  Data Presentation through Natural Scenes , 2005 .

[12]  Chris Weaver.  Building Highly-Coordinated Visualizations in Improvise , 2004 .

[13]  Haim Levkowitz,et al.  Iconographic integrated displays of multiparameter spatial distributions , 1990, Other Conferences.

[14]  Matthew O. Ward,et al.  XmdvTool: integrating multiple methods for visualizing multivariate data , 1994, Proceedings Visualization '94.

[15]  Steven F. Roth,et al.  On the semantics of interactive visualizations , 1996, Proceedings IEEE Symposium on Information Visualization '96.

[16]  Haim Levkowitz,et al.  Perceptual Issues in Visualization , 1995, IFIP Series on Computer Graphics.

[17]  Haim Levkowitz,et al.  Harnessing Preattentive Perceptual Processes in Visualization , 1995, Perceptual Issues in Visualization.

[18]  Andreas Wierse,et al.  Information Visualization in Data Mining and Knowledge Discovery , 2001 .