Name
Abstract | ||
|---|---|---|
Despite years of research yielding systems and guidelines to aid visualization design, practitioners still face the challenge of identifying the best visualization for a given dataset and task. One promising approach to circumvent this problem is to leverage perceptual laws to quantitatively evaluate the effectiveness of a visualization design. Following previously established methodologies, we conduct a large scale (n = 1687) crowdsourced experiment to investigate whether the perception of correlation in nine commonly used visualizations can be modeled using Weber's law. The results of this experiment contribute to our understanding of information visualization by establishing that: (1) for all tested visualizations, the precision of correlation judgment could be modeled by Weber's law, (2) correlation judgment precision showed striking variation between negatively and positively correlated data, and (3) Weber models provide a concise means to quantify, compare, and rank the perceptual precision afforded by a visualization. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TVCG.2014.2346979 | Visualization and Computer Graphics, IEEE Transactions |
Keywords | Field | DocType |
data visualisation,human factors,outsourcing,psychology,Weber law,Weber models,correlation judgment precision,correlation perception,correlation visualization ranking,information visualization,large-scale crowdsourced experiment,negatively correlated data,perceptual laws,perceptual precision comparison,perceptual precision quantification,perceptual precision ranking,positively correlated data,quantitative visualization design effectiveness evaluation,Evaluation,Perception,Visualization | Data mining,Data modeling,Computer science,Crowdsourcing,Artificial intelligence,Law,Computer vision,Data visualization,Information visualization,Ranking,Visualization,Correlation,Perception | Journal |
Volume | Issue | ISSN |
20 | 12 | 1077-2626 |
Citations | PageRank | References |
58 | 1.82 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lane Harrison | 1 | 243 | 20.22 |
| Fumeng Yang | 2 | 65 | 4.93 |
| Steven Franconeri | 3 | 263 | 17.77 |
| Remco Chang | 4 | 983 | 64.96 |