The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Understanding charts and graphs
Abstract
Many charts and graphs do not convey information effectively. This article develops a way of analysing the information in charts and graphs that reveals the design flaws in the display. The analytic scheme requires isolating four types of constituents in a display, and specifying their structure and interrelations at a syntactic, semantic, and pragmatic level of analysis. As the description is constructed, one checks for violations of ‘acceptability principles’, which are derived from facts about human visual information processing and from an analysis of the nature of symbols. Violations of these principles reveal the source of potential difficulties in using a display.
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Citations
Cites
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Cited by
External cognition: how do graphical representations work?
Scaife, M., & Rogers, Y. (1996) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1996.0048 · Cited by 1,066
Making Sense of Graphs: Critical Factors Influencing Comprehension and Instructional Implications
Friel, S. N., Curcio, F. R., & Bright, G. W. (2001) · Journal for Research in Mathematics Education · doi:10.2307/749671 · Cited by 819
Principles and procedures of exploratory data analysis.
Behrens, J. T. (1997) · Psychological Methods · doi:10.1037/1082-989x.2.2.131 · Cited by 465
Review of Graph Comprehension Research: Implications for Instruction
Shah, P., & Hoeffner, J. (2002) · Educational Psychology Review · doi:10.1023/a:1013180410169 · Cited by 431
Visual task characterization for automated visual discourse synthesis
Zhou, M. X., & Feiner, S. K. (1998) · Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '98 · doi:10.1145/274644.274698 · Cited by 207
Task-based effectiveness of basic visualizations
Saket, B., Endert, A., & Demiralp, C. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2018.2829750 · Cited by 178
Benefitting InfoVis with Visual Difficulties
Hullman, J., Adar, E., & Shah, P. (2011) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.175 · Cited by 159
Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content
Lundgard, A., & Satyanarayan, A. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2021.3114770 · Cited by 155
Naïve Cartography: How Intuitions about Display Configuration Can Hurt Performance
Hegarty, M., Smallman, H. S., Stull, A. T., & Canham, M. S. (2009) · Cartographica · doi:10.3138/carto.44.3.171 · Cited by 115
Verbal and visual causal arguments
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A Bayesian Cognition Approach to Improve Data Visualization
Kim, Y.-S., Walls, L. A., Krafft, P., & Hullman, J. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300912 · Cited by 76
SoundBar: exploiting multiple views in multimodal graph browsing
McGookin, D. K., & Brewster, S. A. (2006) · Proceedings of the 4th Nordic conference on Human-computer interaction: changing roles · doi:10.1145/1182475.1182491 · Cited by 41
A Learning Progression for Constructing and Interpreting Data Display
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Metadata
- Authors
- Kosslyn, S. M.
- Venue
- Applied Cognitive Psychology
- Publisher
- Wiley
- Published
- 1989-07
- Volume
- 3
- Issue
- 3
- Pages
- 185-225
- ISSN
- 0888-4080 (ISSN-L)
- 1099-0720
- OpenAlex
- W1972170794
- Cited by
- 449
- References
- 3
- FWCI
- 7.09
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.