Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915552975388672 |
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| author | Proma, Rifat Ara Correll, Michael Quadri, Ghulam Jilani Rosen, Paul |
| author_facet | Proma, Rifat Ara Correll, Michael Quadri, Ghulam Jilani Rosen, Paul |
| contents | Line charts surface many features in time series data, from trends to periodicity to peaks and valleys. However, not every potentially important feature in the data may correspond to a visual feature which 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 ~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 Replicator attempted to retain all major features of the line chart including noise; the Trend Keeper prioritized trends disregarding periodicity and peaks; and the De-noiser filtered out noise while preserving other features. Further, we found that participants tended to faithfully retain trends and peaks and valleys when these features were present, while 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, pre-processing, or clustering time series data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_11927 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts Proma, Rifat Ara Correll, Michael Quadri, Ghulam Jilani Rosen, Paul Human-Computer Interaction Graphics Line charts surface many features in time series data, from trends to periodicity to peaks and valleys. However, not every potentially important feature in the data may correspond to a visual feature which 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 ~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 Replicator attempted to retain all major features of the line chart including noise; the Trend Keeper prioritized trends disregarding periodicity and peaks; and the De-noiser filtered out noise while preserving other features. Further, we found that participants tended to faithfully retain trends and peaks and valleys when these features were present, while 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, pre-processing, or clustering time series data. |
| title | Visual Stenography: Feature Recreation and Preservation in Sketches of Noisy Line Charts |
| topic | Human-Computer Interaction Graphics |
| url | https://arxiv.org/abs/2510.11927 |