The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
How Information Visualization Novices Construct Visualizations
Abstract
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.
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(2001) · Cited by 25,534
Norman, D. (2016) · Vahlen eBooks · doi:10.15358/9783800648108 · Cited by 6,374
The eyes have it: a task by data type taxonomy for information visualizations
Shneiderman, B. (2002) · Proceedings 1996 IEEE Symposium on Visual Languages · doi:10.1109/vl.1996.545307 · Cited by 4,535
Readings in Information Visualization: Using Vision to Think
Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999) · Cited by 3,935
(2013) · Information Visualization · doi:10.1016/b978-0-12-381464-7.00018-1 · Cited by 3,742
(2014) · Choice Reviews Online · doi:10.5860/choice.51-5559 · Cited by 2,342
Automating the design of graphical presentations of relational information
Mackinlay, J. (1986) · ACM Transactions on Graphics · doi:10.1145/22949.22950 · Cited by 1,610
Toward a Deeper Understanding of the Role of Interaction in Information Visualization
Yi, J. S., Kang, Y. A., Stasko, J., & Jacko, J. A. (2007) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2007.70515 · Cited by 1,031
ManyEyes: a Site for Visualization at Internet Scale
Viegas, F. B., Wattenberg, M., van Ham, F., Kriss, J., & McKeon, M. (2007) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2007.70577 · Cited by 720
Design galleries: a general approach to setting parameters for computer graphics and animation
Marks, J., Ruml, W., Ryall, K., Seims, J., Shieber, S., Andalman, B., Beardsley, P. A., Freeman, W., Gibson, S., Hodgins, J., et al. (1997) · Proceedings of the 24th annual conference on Computer graphics and interactive techniques - SIGGRAPH '97 · doi:10.1145/258734.258887 · Cited by 551
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Empirical Studies in Information Visualization: Seven Scenarios
Lam, H., Bertini, E., Isenberg, P., Plaisant, C., & Carpendale, S. (2012) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.279 · Cited by 623
Eviza: A Natural Language Interface for Visual Analysis
Setlur, V., Battersby, S. E., Tory, M., Gossweiler, R., & Chang, A. X. (2016) · Proceedings of the 29th Annual Symposium on User Interface Software and Technology · doi:10.1145/2984511.2984588 · Cited by 231
Self-citationUnderstanding self-reflection: how people reflect on personal data through visual data exploration
Choe, E. K., Lee, B., Zhu, H., Riche, N. H., & Baur, D. (2017) · Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare · doi:10.1145/3154862.3154881 · Cited by 194
Constructing Visual Representations: Investigating the Use of Tangible Tokens
Huron, S., Jansen, Y., & Carpendale, S. (2014) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2014.2346292 · Cited by 141
Accessible Visualization: Design Space, Opportunities, and Challenges
Kim, N. W., Joyner, S. C., Riegelhuth, A., & Kim, Y. (2021) · Computer Graphics Forum · doi:10.1111/cgf.14298 · Cited by 137
Metadata
- Authors
- Grammel, L., Tory, M., & Storey, M.
- Venue
- IEEE Transactions on Visualization and Computer Graphics
- Published
- 2010-11
- Volume
- 16
- Issue
- 6
- Pages
- 943-952
- ISSN
- 1077-2626 (ISSN-L)
- OpenAlex
- W2156440763
- Cited by
- 264
- References
- 34
- FWCI
- 11.06
- Type
- journal article
- Language
- en
- Open access
- closed
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