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How Information Visualization Novices Construct Visualizations
November/December 2010 (vol. 16 no. 6)
pp. 943-952
Lars Grammel, University of Victoria
Melanie Tory, University of Victoria
Margaret-Anne Storey, University of Victoria
It remains challenging for information visualization novices to rapidly construct visualizations during exploratory data analysis. We conducted an exploratory laboratory study in which information visualization novices explored fictitious sales data by communicating visualization specifications to a human mediator, who rapidly constructed the visualizations using commercial visualization software. We found that three activities were central to the iterative visualization construction process: data attribute selection, visual template selection, and visual mapping specification. The major barriers faced by the participants were translating questions into data attributes, designing visual mappings, and interpreting the visualizations. Partial specification was common, and the participants used simple heuristics and preferred visualizations they were already familiar with, such as bar, line and pie charts. We derived abstract models from our observations that describe barriers in the data exploration process and uncovered how information visualization novices think about visualization specifications. Our findings support the need for tools that suggest potential visualizations and support iterative refinement, that provide explanations and help with learning, and that are tightly integrated into tool support for the overall visual analytics process.

[1] Robert Amar, James Eagan, and John T. Stasko, Low-level components of analytic activity in information visualization. In IEEE Symposium on Information Visualization, 2005. INFOVIS 2005, pages 111–117, 2005.
[2] Robert Amar and John T. Stasko, Knowledge precepts for design and evaluation of information visualizations. IEEE Transactions on Visualization and Computer Graphics, pages 432–442, 2005.
[3] Stuart Card, Jock Mackinlay, and Ben Shneiderman editors. Readings in information visualization: using vision to think. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1999.
[4] Stephen Casner, Task-analytic design of graphic presentations. PhD thesis, Pittsburgh, PA, USA, 1990.
[5] Ed Chi, A taxonomy of visualization techniques using the data state reference model. In IEEE Symposium on Information Visualization,2000. InfoVis 2000, pages 69–75, 2000.
[6] Ed Chi, and John Riedl, An operator interaction framework for visualization systems. In INFOVIS '98: Proceedings of the 1998 IEEE Symposium on Information Visualization, pages 63–70, Washington, DC, USA, 1998. IEEE Computer Society.
[7] John W. Creswell, Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Pearson/Merrill Prentice Hall, 2007.
[8] Geoffrey Ellis and Alan Dix, A taxonomy of clutter reduction for information visualisation. IEEE Transactions on Visualization and Computer Graphics, 13 (6): 1216–1223, 2007.
[9] Stephen Few, Now you see it: Simple Visualization Techniques for Quantitative Analysis. Analytics Press, 2009.
[10] Owen Gilson, Nuno Silva, Phil W. Grant, and Min Chen, From web data to visualization via ontology mapping. In Computer Graphics Forum, volume 27, pages 959–966. Blackwell Publishing Ltd, 2008.
[11] David Gotz and Zhen Wen, Behavior-driven visualization recommendation. In IUI ‘09: Proceedings of the 13th international conference on Intelligent user interfaces, pages 315–324, ACM, New York, NY, USA, 2009.
[12] David Gotz and Michelle X. Zhou, Characterizing users' visual analytic activity for insight provenance. Information Visualization, 8 (1): 42–55, 2009.
[13] Jeffrey Heer and Maneesh Agrawala, Multi-scale banking to 45 degrees. IEEE Transactions on Visualization and Computer Graphics, 12 (5): 701–708, 2006.
[14] Jeffrey Heer, Frank van Ham, Sheelagh Carpendale, Chris Weaver, and Petra Isenberg, Creation and collaboration: Engaging new audiences for information visualization, in Information Visualization: Human-Centered Issues and Perspectives, pages 92–133, Springer, Berlin/Heidelberg, 2008.
[15] Jeffrey Heer, Jock D. Mackinlay, Chris Stolte, and Maneesh Agrawala, Graphical Histories for Visualization: Supporting Analysis, Communication, and Evaluation. In IEEE Transactions on Visualization and Computer Graphics, 14 (6): 1189–1196, 2008.
[16] Petra Isenberg, Anthony Tang, and Sheelagh Carpendale, An exploratory study of visual information analysis. In CHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, pages 1217–1226, ACM, New York, NY, USA, 2008.
[17] Chris Johnson, Robert Moorehead, Tamara Munzner, Hanspeter Pfister, Penny Rheingans, and Terry S. Yoo, NIH-NSF Visualization Research Challenges Report, 2006.
[18] Youn-ah Kang, Carsten GÖrg, and John Stasko, Evaluating Visual Analytics Systems for Investigative Analysis: Deriving Design Principles from a Case Study. IEEE VAST, pages 139–146, 2009.
[19] Alfred Kobsa, An empirical comparison of three commercial information visualization systems. In Proceedings of the IEEE Symposium on Information Visualization, page 123, 2001.
[20] Maria Kozhevnikov, Stephen Kosslyn, and Jennifer Shephard, Spatial versus object visualizers: A new characterization of visual cognitive style. Memory & cognition, 33 (4): 710, 2005.
[21] Heidi Lam, A frameworkof interaction costs in information visualization. IEEEtransactions on visualization and computer graphics, 14 (6): 1149–1156, 2008.
[22] Jock D. Mackinlay, Automating the design of graphical presentations of relational information. ACM Transactions on GraphicsTOG), 5 (2): 110–141, 1986.
[23] Jock D. Mackinlay, Pat Hanrahan, and Chris Stolte, Show Me: Automatic presentation for visual analysis. IEEE Transactions on Visualization and Computer Graphics, 13 (6): 1137–1144, 2007.
[24] J. Marks, B. Andalman, PA Beardsley, W. Freeman, S. Gibson, J. Hodgins, T. Kang, B. Mirtich, H. Pfister, W. Ruml et al. , Design galleries: A general approach to setting parameters for computer graphics and animation. In Proceedings of the 24th annual conference on Computer graphics and interactive techniques, pages 389–400. ACM Press/Addison-Wesley Publishing Co. New York, NY, USA, 1997.
[25] Lance A. Miller, Natural Language Programming: Styles, Strategies, and Contrasts. IBM Systems Journal, 20 (2): 184–215, 1981.
[26] Vibhu O. Mittal, Johanna D. Moore, Guiseppe Carenini, and Steven F. Roth, Describing complex charts in natural language: A caption generation system. Computational Linguistics, 24 (3): 431–467, 1998.
[27] Donald A. Norman, The Design of Everyday Things. New York: Doubleday, 1990.
[28] John F. Pane, Brad A. Myers, and Chotirat A. Ratanamahatana, Studying the language and structure in non-programmers' solutions to programming problems. Int. J. Hum.-Comput. Stud., 54 (2): 237–264, 2001.
[29] Peter Pirolli and Stuart Card, The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In Proceedings of International Conference on Intelligence Analysis, 2005.
[30] Zachary Pousman, John T. Stasko, and Michael Mateas, Casual information visualization: Depictions of data in everyday life. IEEE Transactions on Visualization and Computer Graphics, 13 (6): 1145–1152, 2007.
[31] A. Johannes Pretorius and Jarke J. van Wijk, What does the user want to see? What do the data want to be? Information Visualization, 8 (3): 153–166, 2009.
[32] Anthony C. Robinson, Collaborative synthesis of visual analytic results. In Visual Analytics Science and Technology,2008. VAST'08. IEEE Symposium on, pages 67–74, 2008.
[33] Steven F. Roth and Joe Mattis, Automating the presentation of information. In Seventh IEEE Conference on Artificial Intelligence Applications, 1991.
[34] Ben Shneiderman, The eyes have it: A task by data type taxonomy for information visualizations. In VL '96: Proceedings of the 1996 IEEE Symposium on Visual Languages, pages 336–343, IEEE Computer Society, Washington, DC, USA, 1996.
[35] Robert Spence, Information Visualization, Pearson Education Ltd., Harlow, England, 2001.
[36] Chris Stolte, Diane Tang and Pat Hanrahan. Polaris: a system for query, analysis, and visualization of multidimensional databases. In In Communications of the ACM, 51 (11): 75–84, 2008
[37] Fernanda B. Viégas, Martin Wattenberg, Frank van Ham, Jesse Kriss, Matt McKeon, Manyeyes: a site for visualization at internet scale. IEEE Transactions on Visualization and Computer Graphics, 13 (6): 1121–1128, 2007.
[38] Colin Ware, Information Visualization: Perception for Design. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2004.
[39] Chris Weaver, David Fyfe, Anthony Robinson, Deryck Holdsworth, Donna Peuquet, and Alan M. MacEachren, Visual analysis of historic hotel visitation patterns. In 2006 IEEE Symposium On Visual Analytics Science And Technology, pages 35–42, 2006.
[40] Ji Soo Yi, Youn ah Kang, John T. Stasko, and Julie A. Jacko, Toward a deeper understanding of the role of interaction in information visualization. IEEE Transactions on Visualization and Computer Graphics, 13 (6): 1224–1231, 2007

Index Terms:
Empirical study, visualization, visualization construction, visual analytics, visual mapping, novices
Lars Grammel, Melanie Tory, Margaret-Anne Storey, "How Information Visualization Novices Construct Visualizations," IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 943-952, Nov.-Dec. 2010, doi:10.1109/TVCG.2010.164
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