Evaluating the Effect of Style in Information Visualization

This paper reports on a between-subject, comparative online study of three information visualization demonstrators that each displayed the same dataset by way of an identical scatterplot technique, yet were different in style in terms of visual and interactive embellishment. We validated stylistic adherence and integrity through a separate experiment in which a small cohort of participants assigned our three demonstrators to predefined groups of stylistic examples, after which they described the styles with their own words. From the online study, we discovered significant differences in how participants execute specific interaction operations, and the types of insights that followed from them. However, in spite of significant differences in apparent usability, enjoyability and usefulness between the style demonstrators, no variation was found on the self-reported depth, expert-rated depth, confidence or difficulty of the resulting insights. Three different methods of insight analysis have been applied, revealing how style impacts the creation of insights, ranging from higher-level pattern seeking to a more reflective and interpretative engagement with content, which is what underlies the patterns. As this study only forms the first step in determining how the impact of style in information visualization could be best evaluated, we propose several guidelines and tips on how to gather, compare and categorize insights through an online evaluation study, particularly in terms of analyzing the concise, yet wide variety of insights and observations in a trustworthy and reproducable manner.

[1]  John T. Stasko,et al.  Casual Information Visualization: Depictions of Data in Everyday Life , 2007, IEEE Transactions on Visualization and Computer Graphics.

[2]  Martin Wattenberg,et al.  Artistic Data Visualization: Beyond Visual Analytics , 2007, HCI.

[3]  Noam Tractinsky,et al.  Toward the Study of Aesthetics in Information Technology , 2004, ICIS.

[4]  Virginia I. Postrel,et al.  The Substance of Style: How the Rise of Aesthetic Value Is Remaking Commerce, Culture, and Consciousness , 2003 .

[5]  Andrew Vande Moere,et al.  The Effect of Aesthetic on the Usability of Data Visualization , 2007, 2007 11th International Conference Information Visualization (IV '07).

[6]  M. Sheelagh T. Carpendale,et al.  Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations , 2009, IEEE Transactions on Visualization and Computer Graphics.

[7]  Martin Wattenberg,et al.  ManyEyes: a Site for Visualization at Internet Scale , 2007, IEEE Transactions on Visualization and Computer Graphics.

[8]  Mikael Jern Collaborative Web-Enabled GeoAnalytics Applied to OECD Regional Data , 2009, CDVE.

[9]  Mor Naaman,et al.  Playable data: characterizing the design space of game-y infographics , 2011, CHI.

[10]  Joachim Meyer,et al.  Chartjunk or Goldgraph? Effects of Presentation Objectives and Content Desirability on Information Presentation , 1999, MIS Q..

[11]  Chris North,et al.  Toward measuring visualization insight , 2006, IEEE Computer Graphics and Applications.

[12]  Stephen A. Brewster,et al.  The effect of aesthetically pleasing composition on visual search performance , 2010, NordiCHI.

[13]  John T. Stasko,et al.  Understanding and characterizing insights: how do people gain insights using information visualization? , 2008, BELIV.

[14]  Donald A. Norman,et al.  Emotion & design: attractive things work better , 2002, INTR.

[15]  M. Sheelagh T. Carpendale,et al.  Grounded evaluation of information visualizations , 2008, BELIV.

[16]  H. Rosling,et al.  Visual technology unveils the beauty of statistics and swaps policy from dissemination to access , 2007 .

[17]  Silvia Miksch,et al.  Evaluating an InfoVis Technique Using Insight Reports , 2007, 2007 11th International Conference Information Visualization (IV '07).

[18]  Mohit Prasad Poetry on the road , 2008 .

[19]  Chris North,et al.  A comparison of benchmark task and insight evaluation methods for information visualization , 2011, Inf. Vis..

[20]  Carl Gutwin,et al.  Useful junk?: the effects of visual embellishment on comprehension and memorability of charts , 2010, CHI.

[21]  Andrew Vande Moere,et al.  Towards a Model of Information Aesthetics in Information Visualization , 2007, 2007 11th International Conference Information Visualization (IV '07).

[22]  William Ribarsky,et al.  Defining Insight for Visual Analytics , 2009, IEEE Computer Graphics and Applications.

[23]  William Ribarsky,et al.  Toward effective insight management in visual analytics systems , 2009, 2009 IEEE Pacific Visualization Symposium.

[24]  Masaaki Kurosu,et al.  Apparent usability vs. inherent usability: experimental analysis on the determinants of the apparent usability , 1995, CHI 95 Conference Companion.

[25]  Robert Kosara,et al.  Visualization Criticism - The Missing Link Between Information Visualization and Art , 2007, 2007 11th International Conference Information Visualization (IV '07).

[26]  Joachim Meyer,et al.  Chartjunk or goldgraph? Effects of persenataion objectives and content desirability on information presentation: effects of presentation objectives and content desirability on information presentation , 1999 .

[27]  N. Tractinsky,et al.  What is beautiful is usable , 2000, Interact. Comput..