Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts

Line charts surface many features in time series data, from trends to periodicity to peaks & valleys. However, not every potentially important feature in the data may correspond to a visual feature that readers can detect or prioritize. In this study, we conducted a visual stenography task, where participants re-drew line charts to solicit information about the visual features they believed to be important. We systematically varied noise levels (SNR $\approx$≈ 5-30 dB) across line charts to observe how visual clutter influences which features people prioritize in their sketches. We identified three key strategies that correlated with the noise present in the stimuli: the $\color{green}{\textit{Replicator}}$greenReplicator attempted to retain all major features of the line chart including noise; the $\color{yellow}{\textit{Trend Keeper}}$yellowTrendKeeper prioritized trends disregarding periodicity and peaks; and the $\color{pink}{\textit{De-noiser}}$pinkDe-noiser filtered out noise while preserving other features. Further, we found that participants tended to faithfully retain trends and peaks & valleys when these features were present, whereas periodicity and noise were represented in more qualitative or gestural ways: semantically rather than accurately. These results suggest a need to consider more flexible and human-centric ways of presenting, summarizing, preprocessing, or clustering time series data.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-10-27
DOI
https://doi.org/10.1109/tvcg.2025.3626128
Primary Topic
Translation Studies and Practices
Type
article
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article

Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts

Ghulam Jilani Quadri, Paul Rosen, Michael Correll, Rifat Ara Proma
IEEE Transactions on Visualization and Computer Graphics
Translation Studies and Practices
article

Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts

Ghulam Jilani Quadri, Paul Rosen, Michael Correll, Rifat Ara Proma
article en

Abstract

Line charts surface many features in time series data, from trends to periodicity to peaks & valleys. However, not every potentially important feature in the data may correspond to a visual feature that readers can detect or prioritize. In this study, we conducted a visual stenography task, where participants re-drew line charts to solicit information about the visual features they believed to be important. We systematically varied noise levels (SNR $\approx$≈ 5-30 dB) across line charts to observe how visual clutter influences which features people prioritize in their sketches. We identified three key strategies that correlated with the noise present in the stimuli: the $\color{green}{\textit{Replicator}}$greenReplicator attempted to retain all major features of the line chart including noise; the $\color{yellow}{\textit{Trend Keeper}}$yellowTrendKeeper prioritized trends disregarding periodicity and peaks; and the $\color{pink}{\textit{De-noiser}}$pinkDe-noiser filtered out noise while preserving other features. Further, we found that participants tended to faithfully retain trends and peaks & valleys when these features were present, whereas periodicity and noise were represented in more qualitative or gestural ways: semantically rather than accurately. These results suggest a need to consider more flexible and human-centric ways of presenting, summarizing, preprocessing, or clustering time series data.

IEEE Transactions on Visualization and Computer GraphicsVol. 32(2)
Northeastern University (US), University of Utah (US), University of Oklahoma (US)
Openalex Percentile: Top 62%
Translation Studies and Practices
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Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts — Ghulam Jilani Quadri, Paul Rosen, et al. · IEEE Transactions on Visualization and Computer Graphics (2025) | TGRS Research Map | TGRS