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Lookup NU author(s): Dr Sara Fernstad, Lucy Mclaughlin, Dr Mike Simpson
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 Society for Imaging Science and Technology. All rights reserved.The natural ordering of shapes is not historically used in visualization applications. It could be helpful to show if an order exists among shapes, as this would provide an additional visual channel for presenting ordered bivariate data. Objective—we rigorously evaluate the use of visual entropy allowing us to construct an ordered scale of shape glyphs. Method—we evaluate the visual entropy glyphs in replicated trials online and at two different global locations. Results—an exact binomial analysis of a pairwise comparison of the glyphs showed a majority of participants (n = 87) ordered the glyphs as predicted by the visual entropy score with large effect size. In a further signal detection experiment participants (n = 15) were able to find glyphs representing uncertainty with high sensitivity and low error rates. Conclusion—Visual entropy predicts shape order and provides a visual channel with the potential to support ordered bivariate data.
Author(s): Holliman NS, Coltekin A, Fernstad SJ, McLaughlin L, Simpson MD, Woods AJ
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: IS and T International Symposium on Electronic Imaging Science and Technology
Year of Conference: 2024
Pages: HVEI-206
Online publication date: 01/01/2024
Acceptance date: 02/04/2023
Date deposited: 05/03/2024
Publisher: Society for Imaging Science and Technology
URL: https://doi.org/10.2352/EI.2024.36.11.HVEI-206
DOI: 10.2352/EI.2024.36.11.HVEI-206
