Sampling-based Visualization
Sampling-Based Visualization is a visualization approach that employs statistical sampling techniques to generate representative subsets of data for visual representation, thereby enabling efficient exploration and analysis of large and complex datasets while preserving underlying structural properties.
30
Publications
1.3K
Citations
90
Authors
40
Institutions
Publications per year
2017–2026
11
Parents
30
Visualization-aware sampling for very large databases
Yongjoo Park, Michael Cafarella, Barzan Mozafari · 2016 · 116 citations
Rapid sampling for visualizations with ordering guarantees
Albert Kim, Eric Blais, Aditya Parameswaran et al. · Proceedings of the VLDB Endowment · 2015 · 102 citations · Full text
anesthetic: nested sampling visualisation
The Journal of Open Source Software · 2019 · 92 citations · Full text
Effectively Visualizing Large Networks Through Sampling
Davood Rafiei, Stephen Curial · 2006 · 79 citations
1–5 of 30
90
3
h-index
3
h-index
3
h-index
2
h-index
2
h-index
1–5 of 90
40

Sapienza University of Rome
Rome, Italy
4 h-index
7 publications
259 citations
Lancaster University
Lancaster, United Kingdom
3 h-index
4 publications
164 citations

University of Huddersfield
Huddersfield, United Kingdom
2 h-index
2 publications
102 citations

Tel Aviv University
Tel Aviv, Israel
2 h-index
2 publications
171 citations

University of Waterloo
Waterloo, Canada
2 h-index
2 publications
171 citations
The Ohio State University
Columbus, United States
2 h-index
7 publications
134 citations
Moscow Institute of Thermal Technology
Moscow, Russia
2 h-index
4 publications
375 citations

University of Alberta
Edmonton, Canada
2 h-index
2 publications
119 citations
1–8 of 40
TVCG · 4 publications · 221 citations
4
h-index
PVLDB · 2 publications · 171 citations
2
h-index
1 publications · 28 citations
1
h-index
1 publications · 46 citations
1
h-index
1 publications · 18 citations
1
h-index
1–5