Paper Info
Title
Value and relation display: interactive visual exploration of large data sets with hundreds of dimensions.
Abstract
Few existing visualization systems can handle large data sets with hundreds of dimensions, since high-dimensional data sets cause clutter on the display and large response time in interactive exploration. In this paper, we present a significantly improved multidimensional visualization approach named Value and Relation (VaR) display that allows users to effectively and efficiently explore large data sets with several hundred dimensions. In the VaR display, data values and dimension relationships are explicitly visualized in the same display by using dimension glyphs to explicitly represent values in dimensions and glyph layout to explicitly convey dimension relationships. In particular, pixel-oriented techniques and density-based scatterplots are used to create dimension glyphs to convey values. Multidimensional scaling, Jigsaw map hierarchy visualization techniques, and an animation metaphor named Rainfall are used to convey relationships among dimensions. A rich set of interaction tools has been provided to allow users to interactively detect patterns of interest in the VaR display. A prototype of the VaR display has been fully implemented. The case studies presented in this paper show how the prototype supports interactive exploration of data sets of several hundred dimensions. A user study evaluating the prototype is also reported in this paper.
Year
DOI
Venue
2007
10.1109/TVCG.2007.1010
IEEE Trans. Vis. Comput. Graph.
Keywords
Field
DocType
hundred dimension,relation display,high-dimensional data,large data sets,interactive exploration,large data set,dimension relationship,dimension glyphs,existing visualization system,interactive visual exploration,data value,var display,rainfall,computer animation,data visualisation,visual system,visual analytics,high dimensional data,human computer interaction,interactive visualization,multidimensional scaling
Glyph,Computer vision,Data visualization,Data set,Multidimensional scaling,Computer graphics (images),Visualization,Computer science,Visual analytics,Animation,Artificial intelligence,Computer animation
Journal
Volume
Issue
ISSN
13
3
1077-2626
Citations 
PageRank 
References 
32
1.28
24
Authors
5
Name
Order
Citations
PageRank
Jing Yang123913.46
Daniel Hubball2763.46
Matthew O. Ward31757189.48
Elke A. Rundensteiner44076700.65
William Ribarsky52057157.91