An experiment in graphical perception
International Journal of Man-Machine Studies
The visual display of quantitative information
The visual display of quantitative information
Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
Information Visualization: Perception for Design
Information Visualization: Perception for Design
Evaluating Visualizations: Do Expert Reviews Work?
IEEE Computer Graphics and Applications
How to Lie With Statistics
Using Visual Design Experts in Critique-Based Evaluation of 2D Vector Visualization Methods
IEEE Transactions on Visualization and Computer Graphics
It's easy to produce chartjunk using Microsoft®Excel 2007 but hard to make good graphs
Computational Statistics & Data Analysis
A Survey of Radial Methods for Information Visualization
IEEE Transactions on Visualization and Computer Graphics
Useful junk?: the effects of visual embellishment on comprehension and memorability of charts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Uncovering Strengths and Weaknesses of Radial Visualizations---an Empirical Approach
IEEE Transactions on Visualization and Computer Graphics
An Extension of Wilkinson’s Algorithm for Positioning Tick Labels on Axes
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Eye tracking for visualization evaluation: reading values on linear versus radial graphs
Information Visualization - Special issue on Evaluation for Information Visualization
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It is difficult to create appropriate bar charts for data that cover large value ranges. The usual approach for these cases employs a logarithmic scale, which, however, suffers from issues inherent to its non-linear mapping: for example, a quantitative comparison of different values is difficult. We present a new approach for bar charts that combines the advantages of linear and logarithmic scales, while avoiding their drawbacks. Our scale-stack bar charts use multiple scales to cover a large value range, while the linear mapping within each scale preserves the ability to visually compare quantitative ratios. Scale-stack bar charts can be used for the same applications as classic bar charts; in particular, they can readily handle stacked bar representations and negative values. Our visualization technique is demonstrated with results for three different application areas and is assessed by an expert review and a quantitative user study confirming advantages of our technique for quantitative comparisons.