Perceptual Evaluation of Common Line Variables for Displaying Uncertainty on Molecular Surfaces
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Data are often subject to some degree of uncertainty, whether aleatory or epistemic. This applies both to experimental data acquired with sensors as well as to simulation data. Displaying these data and their uncertainty faithfully is crucial for gaining knowledge. Specifically, the effective communication of the uncertainty can influence the interpretation of the data and the users' trust in the visualization. However, uncertainty-aware visualization has gotten little attention in molecular visualization. When using the established molecular representations, the physicochemical attributes of the molecular data usually already occupy the common visual channels like shape, size, and color. Consequently, to encode uncertainty information, we need to open up another channel by using feature lines. Even though various line variables have been proposed for uncertainty visualizations, they have so far been primarily used for two-dimensional data and there has been little perceptual evaluation. Therefore, we conducted a perceptual study to determine the suitability of the line variables sketchiness, dashing, grayscale, and width for distinguishing several uncertainty values on molecular surfaces.
Description
CCS Concepts: Human-centered computing --> Empirical studies in visualization; Scientific visualization; Computing methodologies --> Non-photorealistic rendering; Applied computing --> Imaging"
@inproceedings{10.2312:vcbm.20221186,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {Renata G. Raidou and Björn Sommer and Torsten W. Kuhlen and Michael Krone and Thomas Schultz and Hsiang-Yun Wu},
title = {{Perceptual Evaluation of Common Line Variables for Displaying Uncertainty on Molecular Surfaces}},
author = {Sterzik, Anna and Lichtenberg, Nils and Krone, Michael and Cunningham, Douglas W. and Lawonn, Kai},
year = {2022},
publisher = {The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-177-9},
DOI = {10.2312/vcbm.20221186}
}