Visual Encoding Evaluation
Visual Encoding Evaluation is a systematic method for assessing the effectiveness, accuracy, and interpretability of visual representations in conveying data through the mapping of data attributes to visual properties such as position, color, size, and shape.
33
Publications
2.7K
Citations
93
Authors
53
Institutions
Publications per year
2017–2026
13
Parents
33
A Taxonomy of Visual Cluster Separation Factors
Michael Sedlmair, Andrada Tatu, Tamara Munzner et al. · Computer Graphics Forum · 2012 · 159 citations
Kevin Hu, Snehalkumar S. Gaikwad, Madelon Hulsebos et al. · 2019 · 97 citations · Full text
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University of Washington
Seattle, United States
3 h-index
6 publications
644 citations

University of British Columbia
Vancouver, Canada
3 h-index
4 publications
1.3K citations
Georgia Institute of Technology
Atlanta, United States
2 h-index
2 publications
132 citations
Virginia Tech
Blacksburg, United States
2 h-index
3 publications
44 citations

University of Leeds
Leeds, United Kingdom
2 h-index
2 publications
67 citations
Okanagan University College
Kelowna, Canada
1 h-index
1 publications
43 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
1 h-index
2 publications
86 citations
University of Geneva
Geneva, Switzerland
1 h-index
1 publications
39 citations
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TVCG · 7 publications · 1.4K citations
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5 publications · 521 citations
5
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2 publications · 106 citations
2
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Repository · 2 publications · 44 citations
2
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1 publications · 91 citations
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