Comparing Uncertainty Visualizations for a Dynamic Decision-Making Task

Supporting complex decision making requires conveying relevant information characteristics or qualifiers. The authors tested transparency and numeric annotation for displaying uncertainty about object identity. Participants performed a “missile defense” game in which they decided whether to destroy moving objects (which were either threatening missiles or nonthreatening birds and planes) before they reached a city. Participants were provided with uncertain information about the objects’ classifica-tions. Uncertainty was represented through the transparency of icons representing the objects and/or with numeric annotations. Three display methods were created. Icons represented the most likely object classification (with solid icons), the most likely object classification (with icons whose transparency represented the level of uncertainty), or the probability that the icon was a missile (with transparency). In a fourth condition, participants could choose among the representations. Icons either were or were not annotated with numeric probability labels. Task performance was highest when participants could toggle the displays, with little effect of numeric annotation. In conditions in which probabilities were available graphically or numerically, participants chose to engage objects when they were farther from the city and had a lower probability of being a missile. Results provided continued support for the use of graphical uncertainty representations, even when numeric representations are present.

[1]  Alex T. Pang,et al.  Approaches to uncertainty visualization , 1996, The Visual Computer.

[2]  Igor Drecki,et al.  Visualisation of Uncertainty in Geographical Data , 2002 .

[3]  David Howard,et al.  Interface Design for Geographic Visualization: Tools for Representing Reliability , 1996 .

[4]  Stefan Biffl,et al.  PlanningLines: novel glyphs for representing temporal uncertainties and their evaluation , 2005, Ninth International Conference on Information Visualisation (IV'05).

[5]  Alan M. MacEachren,et al.  VISUALIZING UNCERTAIN INFORMATION , 1992 .

[6]  Craig M. Wittenbrink,et al.  Glyphs for visualizing uncertainty in environmental vector fields , 1995 .

[7]  Mark Gahegan,et al.  Visualizing Geospatial Information Uncertainty: What We Know and What We Need to Know , 2005 .

[8]  Daniel C. Cliburn,et al.  Evaluating the Usability of a Tool for Visualizing the Uncertainty of the Future Global Water Balance , 2003 .

[9]  Nahum D. Gershon Visualization of an Imperfect World , 1998, IEEE Computer Graphics and Applications.

[10]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[11]  Alphonse Chapanis Evaluating usability , 1991 .

[12]  Daniel Weiskopf,et al.  Texture-based visualization of uncertainty in flow fields , 2005, VIS 05. IEEE Visualization, 2005..

[13]  Richard T. Stone,et al.  Visual Representations of Meta-Information , 2009 .

[14]  P. Hancock,et al.  Human Mental Workload , 1988 .

[15]  Ross Brown Animated visual vibrations as an uncertainty visualisation technique , 2004, GRAPHITE '04.

[16]  R. Hogarth Insights in Decision Making , 1990 .

[17]  Ann M. Bisantz,et al.  Utilizing Graphical Formats to Convey Uncertainty in a Decision Making Task , 2000 .

[18]  Ann M. Bisantz,et al.  Displaying Uncertainty: Investigating the Effects of Display Format and Specificity , 2005, Hum. Factors.

[19]  Christopher D. Wickens,et al.  Proximity Compatibility and Information Display: Effects of Color, Space, and Objectness on Information Integration , 1990 .

[20]  David V. Budescu,et al.  A review of human linguistic probability processing: General principles and empirical evidence , 1995, The Knowledge Engineering Review.

[21]  Limor Nadav-Greenberg,et al.  The Effect of Uncertainty Visualizations on Decision Making in Weather Forecasting , 2008 .

[22]  Keith C. Clarke,et al.  Testing Popular Visualization Techniques for Representing Model Uncertainty , 2003 .

[23]  Joseph J. Pfeiffer Using Brightness and Saturation to Visualize Belief and Uncertainty , 2002, Diagrams.

[24]  A. Tversky,et al.  Choices, Values, and Frames , 2000 .

[25]  Michael F. Goodchild,et al.  Spatial Data Quality , 2002 .

[26]  Victoria Interrante,et al.  Effectively visualizing multi-valued flow data using color and texture , 2003, IEEE Visualization, 2003. VIS 2003..

[27]  Alex T. Pang,et al.  Glyphs for Visualizing Uncertainty in Vector Fields , 1996, IEEE Trans. Vis. Comput. Graph..

[28]  Victoria Interrante,et al.  Harnessing natural textures for multivariate visualization , 2000, IEEE Computer Graphics and Applications.

[29]  Michael F. Goodchild,et al.  Visualizing spatial data uncertainty using animation , 1997 .