The value of visualization

The field of visualization is getting mature. Many problems have been solved, and new directions are sought for. In order to make good choices, an understanding of the purpose and meaning of visualization is needed. Especially, it would be nice if we could assess what a good visualization is. In this paper an attempt is made to determine the value of visualization. A technological viewpoint is adopted, where the value of visualization is measured based on effectiveness and efficiency. An economic model of visualization is presented, and benefits and costs are established. Next, consequences (brand limitations of visualization are discussed (including the use of alternative methods, high initial costs, subjective/less, and the role of interaction), as well as examples of the use of the model for the judgement of existing classes of methods and understanding why they are or are not used in practice. Furthermore, two alternative views on visualization are presented and discussed: viewing visualization as an art or as a scientific discipline. Implications and future directions are identified.

[1]  Edward R. Tufte,et al.  Envisioning Information , 1990 .

[2]  Colin Ware,et al.  Information Visualization: Perception for Design , 2000 .

[3]  Theresa-Marie Rhyne,et al.  Panel 1: Can We Determine the Top Unresolved Problems of Visualization? , 2004, IEEE Visualization.

[4]  Bill Hibbard,et al.  Top ten visualization problems , 1999, COMG.

[5]  Robert S. Laramee,et al.  The State of the Art in Flow Visualization: Dense and Texture‐Based Techniques , 2004, Comput. Graph. Forum.

[6]  Kristin A. Cook,et al.  Illuminating the Path: The Research and Development Agenda for Visual Analytics , 2005 .

[7]  Pak Chung Wong,et al.  30 Years of Multidimensional Multivariate Visualization , 1994, Scientific Visualization.

[8]  Jarke J. van Wijk,et al.  Image based flow visualization , 2002, ACM Trans. Graph..

[9]  J. van Wijk,et al.  Spot noise texture synthesis for data visualization , 1991, SIGGRAPH.

[10]  Alfred Kobsa User Experiments with Tree Visualization Systems , 2004 .

[11]  David C. Banks,et al.  Counting cases in marching cubes: toward a generic algorithm for producing substitopes , 2003, IEEE Visualization, 2003. VIS 2003..

[12]  Paula Hanger,et al.  To the Death , 1950 .

[13]  Chris R. Johnson Top Scientific Visualization Research Problems , 2004, IEEE Computer Graphics and Applications.

[14]  Ben Shneiderman,et al.  Tree-maps: a space-filling approach to the visualization of hierarchical information structures , 1991, Proceeding Visualization '91.

[15]  Edward Rolf Tufte,et al.  The visual display of quantitative information , 1985 .

[16]  B. Marx The Visual Display of Quantitative Information , 1985 .

[17]  J. V. van Wijk,et al.  Cluster and calendar based visualization of time series data , 1999, Proceedings 1999 IEEE Symposium on Information Visualization (InfoVis'99).

[18]  Robert Michael Kirby,et al.  Quantitative comparative evaluation of 2D vector field visualization methods , 2001, Proceedings Visualization, 2001. VIS '01..

[19]  Jock D. Mackinlay,et al.  Automating the design of graphical presentations of relational information , 1986, TOGS.

[20]  Jarke J. van Wijk,et al.  Rendering hierarchical data , 2003, CACM.

[21]  Brian Cabral,et al.  Imaging vector fields using line integral convolution , 1993, SIGGRAPH.

[22]  Jarke J. van Wijk,et al.  Botanical visualization of huge hierarchies , 2001, IEEE Symposium on Information Visualization, 2001. INFOVIS 2001..

[23]  Melanie Tory,et al.  Human factors in visualization research , 2004, IEEE Transactions on Visualization and Computer Graphics.

[24]  H. Margolis Visual explanations: Images and quantities, evidence and narrative , 1998 .