Issue No. 09 - Sept. (2012 vol. 18)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.279
H. Lam , Google, Inc., Mountain View, CA, USA
E. Bertini , Dept. of Comput. & Inf. Sci., Univ. of Konstanz, Konstanz, Germany
P. Isenberg , INRIA, Univ. Paris-Sud, Orsay, France
C. Plaisant , Univ. of Maryland, College Park, MD, USA
S. Carpendale , Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada
We take a new, scenario-based look at evaluation in information visualization. Our seven scenarios, evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, evaluating visualization algorithms, and evaluating collaborative data analysis were derived through an extensive literature review of over 800 visualization publications. These scenarios distinguish different study goals and types of research questions and are illustrated through example studies. Through this broad survey and the distillation of these scenarios, we make two contributions. One, we encapsulate the current practices in the information visualization research community and, two, we provide a different approach to reaching decisions about what might be the most effective evaluation of a given information visualization. Scenarios can be used to choose appropriate research questions and goals and the provided examples can be consulted for guidance on how to design one's own study.
data visualisation, visualization publications, empirical studies, information visualization, seven scenarios, visual data analysis, visual data reasoning, user performance evaluation, evaluating user experience, evaluating environments, evaluating communication, evaluating visualization algorithms, evaluating collaborative data analysis, Data visualization, Visualization, Data analysis, Encoding, Systematics, Taxonomy, Electronic mail, evaluation., Information visualization
P. Isenberg, E. Bertini, H. Lam, C. Plaisant and S. Carpendale, "Empirical Studies in Information Visualization: Seven Scenarios," in IEEE Transactions on Visualization & Computer Graphics, vol. 18, no. , pp. 1520-1536, 2012.