Höhn, Markus and Wunderlich, Marcel and Ballweg, Kathrin and Landesberger, Tatiana von (2020):
Width-Scale Bar Charts for Data with Large Value Range.
pp. 103-107, EuroVis 2020: 11th International EuroVis Workshop on Visual Analytics, virtual Conference, 25.-29.05.2020, DOI: 10.2312/evs.20201056,
[Conference or Workshop Item]
Abstract
Data sets with large value range are difficult to visualize with traditional linear bar charts. Usually, a logarithmic scale isused in these cases. However, the logarithmic scale suffers from non-linearity. Recently, scale-stack bar charts and magnitudemarkers, improve the readability of values. However, they have other disadvantages such as various scales or several objectsfor visualizing one value. We propose the width-scale bar chart that uses width, height and color to cover a large value rangewithin one linear scale. A quantitative user study shows advantages of our design – especially for reading values.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2020 |
| Creators: | Höhn, Markus and Wunderlich, Marcel and Ballweg, Kathrin and Landesberger, Tatiana von |
| Title: | Width-Scale Bar Charts for Data with Large Value Range |
| Language: | English |
| Abstract: | Data sets with large value range are difficult to visualize with traditional linear bar charts. Usually, a logarithmic scale isused in these cases. However, the logarithmic scale suffers from non-linearity. Recently, scale-stack bar charts and magnitudemarkers, improve the readability of values. However, they have other disadvantages such as various scales or several objectsfor visualizing one value. We propose the width-scale bar chart that uses width, height and color to cover a large value rangewithin one linear scale. A quantitative user study shows advantages of our design – especially for reading values. |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Event Title: | EuroVis 2020: 11th International EuroVis Workshop on Visual Analytics |
| Event Location: | virtual Conference |
| Event Dates: | 25.-29.05.2020 |
| Date Deposited: | 29 May 2020 06:26 |
| DOI: | 10.2312/evs.20201056 |
| Official URL: | https://conferences.eg.org/egev20/program/ |
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