Studying the Separability of Visual Channel Pairs in Symbol Maps
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866908848812457984 |
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| author | Sukumar, Poorna Talkad Porfiri, Maurizio Nov, Oded |
| author_facet | Sukumar, Poorna Talkad Porfiri, Maurizio Nov, Oded |
| contents | Visualizations often encode multivariate data by mapping attributes to distinct visual channels such as color, size, or shape. The effectiveness of these encodings depends on separability--the extent to which channels can be perceived independently. Yet systematic evidence for separability, especially in map-based contexts, is lacking. We present a crowdsourced experiment that evaluates the separability of four channel pairs--color (ordered) x shape, color (ordered) x size, size x shape, and size x orientation--in the context of bivariate symbol maps. Both accuracy and speed analyses show that color x shape is the most separable and size x orientation the least separable, while size x color and size x shape do not differ. Separability also proved asymmetric--performance depended on which channel encoded the task-relevant variable, with color and shape outperforming size, and square shape especially difficult to discriminate. Our findings advance the empirical understanding of visual separability, with implications for multivariate map design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_20022 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Studying the Separability of Visual Channel Pairs in Symbol Maps Sukumar, Poorna Talkad Porfiri, Maurizio Nov, Oded Human-Computer Interaction Visualizations often encode multivariate data by mapping attributes to distinct visual channels such as color, size, or shape. The effectiveness of these encodings depends on separability--the extent to which channels can be perceived independently. Yet systematic evidence for separability, especially in map-based contexts, is lacking. We present a crowdsourced experiment that evaluates the separability of four channel pairs--color (ordered) x shape, color (ordered) x size, size x shape, and size x orientation--in the context of bivariate symbol maps. Both accuracy and speed analyses show that color x shape is the most separable and size x orientation the least separable, while size x color and size x shape do not differ. Separability also proved asymmetric--performance depended on which channel encoded the task-relevant variable, with color and shape outperforming size, and square shape especially difficult to discriminate. Our findings advance the empirical understanding of visual separability, with implications for multivariate map design. |
| title | Studying the Separability of Visual Channel Pairs in Symbol Maps |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.20022 |