@inbook{57edbf1e4b3e4a68a3e0e9d4c3dca52b,
title = "Entropy Ordered Shapes as Bivariate Glyphs",
abstract = "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 pair-wise 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 = "Nicolas Holliman and Arzu {\c C}{\"o}ltekin and Fernstad, {Sara J.} and Lucy McLaughlin and Simpson, {Michael D.} and Woods, {Andrew J.}",
note = "Funding Information: The authors wish to thank: the Alan Turing Institute for funding under EPSRC grant EP/N510129/1 and for Professor Holliman{\textquoteright}s Turing Fellowship; Professor Jenny Read and Dr Kevin Wilson (Newcastle University) for their helpful insights; Northumbria VRV Studio for the VNG 3D model of Newcastle; the EPSRC UKRIC funded Urban Observatory at Newcastle for sensor data; the Curtin HIVE and members of the CIC at Curtin University, Perth, WA; Dr Ronni Bowman (DSTL) and Matt Butchers (KTN) for inspirational workshops on uncertainty visualization for high-level decision makers; all participants who took part in our experiments, and finally, Professor David Firth (Univ. of Warwick) for invaluable advice on statistical methods. A more detailed preprint of this article is available on Arxiv. Publisher Copyright: {\textcopyright} 2024 Society for Imaging Science and Technology. All rights reserved.",
year = "2024",
month = jan,
day = "23",
doi = "10.2352/EI.2024.36.11.HVEI-206",
language = "English",
volume = "36",
series = "IS and T International Symposium on Electronic Imaging Science and Technology",
publisher = "The Society for Imaging Science and Technology",
pages = "206--1 -- 206--10",
booktitle = "Electronic Imaging",
edition = "11",
}