Acquired Codes of Meaning in Data Visualization and Infographics: Beyond Perceptual Primitives

Byrne, Lydia, Angus, Daniel and Wiles, Janet (2016) Acquired Codes of Meaning in Data Visualization and Infographics: Beyond Perceptual Primitives. IEEE Transactions on Visualization and Computer Graphics, 22 1: 509-518. doi:10.1109/TVCG.2015.2467321

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Author Byrne, Lydia
Angus, Daniel
Wiles, Janet
Title Acquired Codes of Meaning in Data Visualization and Infographics: Beyond Perceptual Primitives
Journal name IEEE Transactions on Visualization and Computer Graphics   Check publisher's open access policy
ISSN 1077-2626
Publication date 2016-01-31
Year available 2016
Sub-type Article (original research)
DOI 10.1109/TVCG.2015.2467321
Open Access Status Not Open Access
Volume 22
Issue 1
Start page 509
End page 518
Total pages 10
Place of publication Piscataway, NJ United States
Publisher Institute of Electrical and Electronics Engineers
Language eng
Formatted abstract
While information visualization frameworks and heuristics have traditionally been reluctant to include acquired codes of meaning, designers are making use of them in a wide variety of ways. Acquired codes leverage a user's experience to understand the meaning of a visualization. They range from figurative visualizations which rely on the reader's recognition of shapes, to conventional arrangements of graphic elements which represent particular subjects. In this study, we used content analysis to codify acquired meaning in visualization. We applied the content analysis to a set of infographics and data visualizations which are exemplars of innovative and effective design. 88% of the infographics and 71% of data visualizations in the sample contain at least one use of figurative visualization. Conventions on the arrangement of graphics are also widespread in the sample. In particular, a comparison of representations of time and other quantitative data showed that conventions can be specific to a subject. These results suggest that there is a need for information visualization research to expand its scope beyond perceptual channels, to include social and culturally constructed meaning. Our paper demonstrates a viable method for identifying figurative techniques and graphic conventions and integrating them into heuristics for visualization design.
Keyword Context
Data visualization
Image color analysis
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 3 times in Scopus Article | Citations
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