Scale-Stack Bar Charts
| dc.contributor.author | Hlawatsch, Marcel | en_US |
| dc.contributor.author | Sadlo, Filip | en_US |
| dc.contributor.author | Burch, Michael | en_US |
| dc.contributor.author | Weiskopf, Daniel | en_US |
| dc.contributor.editor | B. Preim, P. Rheingans, and H. Theisel | en_US |
| dc.date.accessioned | 2015-02-28T15:30:29Z | |
| dc.date.available | 2015-02-28T15:30:29Z | |
| dc.date.issued | 2013 | en_US |
| dc.description.abstract | 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. | en_US |
| dc.description.seriesinformation | Computer Graphics Forum | en_US |
| dc.identifier.doi | 10.1111/cgf.12105 | en_US |
| dc.identifier.issn | 1467-8659 | en_US |
| dc.identifier.uri | https://doi.org/10.1111/cgf.12105 | en_US |
| dc.publisher | The Eurographics Association and Blackwell Publishing Ltd. | en_US |
| dc.subject | H.5.0 [Information Interfaces and Presentation] | en_US |
| dc.subject | General | en_US |
| dc.title | Scale-Stack Bar Charts | en_US |