Tree Visualization Scalability
Tree Visualization Scalability is a methodological framework that enables the effective rendering and interactive exploration of hierarchically structured data as tree visualizations, distinguishing itself by maintaining perceptual clarity and navigational efficiency as the size and complexity of the data increase.
7
Publications
540
Citations
28
Authors
17
Institutions
Publications per year
2017–2026
1
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7
Jeffrey Heer, Stuart K. Card · 2004 · 84 citations
BarcodeTree: Scalable Comparison of Multiple Hierarchies
Guozheng Li, Yu Zhang, Yu Dong et al. · IEEE Transactions on Visualization and Computer Graphics · 2019 · 28 citations
Scalable, Robust Visualization of Very Large Trees
Dale Beermann, Tamara Munzner, Greg Humphreys · Eurographics · 2005 · 16 citations · Full text
1–5 of 7
28
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Research Institute of Precision Instruments (Russia), Russia
1 publications · 16 citations
1
h-index
1–5 of 28
17

Western Sydney University
Richmond, Australia
2 h-index
3 publications
33 citations
University of Technology Sydney
Sydney, Australia
2 h-index
5 publications
106 citations
Tianjin University
Tianjin, China
2 h-index
3 publications
33 citations

École de Technologie Supérieure
Montreal, Canada
1 h-index
1 publications
28 citations

Monash University
Melbourne, Australia
1 h-index
1 publications
11 citations
University of Virginia
Charlottesville, United States
1 h-index
2 publications
32 citations

Peking University
Beijing, China
1 h-index
1 publications
28 citations
University of California, Berkeley
Berkeley, United States
1 h-index
1 publications
84 citations
1–8 of 17
Repository · 1 publications · 16 citations
1
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1 publications · 11 citations
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JCIM · 1 publications · 375 citations
1
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TVCG · 1 publications · 28 citations
1
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JVLC · 1 publications · 11 citations
1
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