The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons
Stacked bar charts are a visualization method for presenting multiple attributes of data, and many visualization tools support these charts. To assess the efficacy of stacked bar charts in supporting attribute-comparison tasks, we conducted a user study to compare three types of stacked bar charts:...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2018-09-01
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| Series: | Visual Informatics |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468502X18300287 |
| _version_ | 1811301257935060992 |
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| author | Indratmo Lee Howorko Joyce Maria Boedianto Ben Daniel |
| author_facet | Indratmo Lee Howorko Joyce Maria Boedianto Ben Daniel |
| author_sort | Indratmo |
| collection | DOAJ |
| description | Stacked bar charts are a visualization method for presenting multiple attributes of data, and many visualization tools support these charts. To assess the efficacy of stacked bar charts in supporting attribute-comparison tasks, we conducted a user study to compare three types of stacked bar charts: classical, inverting, and diverging. Each chart type was used to visualize six attributes of data where half of the attributes have the characteristics of ‘lower better’ whereas the other half attributes are with ‘higher better.’ Thirty participants were asked to perform two types of comparison tasks: single-attribute and overall-attribute comparisons. We measured the completion time, error rate, and perceived difficulty of the comparison tasks. The results of the study suggest that, for overall-attribute comparisons, the inverting stacked bar chart was the most effective with regards to the completion time. The results also show that performing overall-attribute comparisons using the classical and diverging stacked bar charts required more time than performing single-attribute comparisons using these charts. Participants perceived the inverting and diverging stacked bar charts as easier-to-use than the classical stacked bar chart for overall-attribute comparisons. However, for single-attribute comparisons, all chart types delivered similar performance. We discuss how these findings can inform the better design of interactive stacked bar charts and visualization tools. Keywords: Stacked bar chart, Comparison task, User study, Multi-attribute data, Information visualization |
| first_indexed | 2024-04-13T07:05:34Z |
| format | Article |
| id | doaj.art-7993fbe5d90248d9a7304a54d5baac52 |
| institution | Directory Open Access Journal |
| issn | 2468-502X |
| language | English |
| last_indexed | 2024-04-13T07:05:34Z |
| publishDate | 2018-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Visual Informatics |
| spelling | doaj.art-7993fbe5d90248d9a7304a54d5baac522022-12-22T02:57:00ZengElsevierVisual Informatics2468-502X2018-09-0123155165The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons Indratmo0Lee Howorko1Joyce Maria Boedianto2Ben Daniel3Department of Computer Science, MacEwan University, Canada; Corresponding author.Department of Computer Science, MacEwan University, CanadaDepartment of Computer Science, MacEwan University, CanadaHigher Education Development Centre, University of Otago, New ZealandStacked bar charts are a visualization method for presenting multiple attributes of data, and many visualization tools support these charts. To assess the efficacy of stacked bar charts in supporting attribute-comparison tasks, we conducted a user study to compare three types of stacked bar charts: classical, inverting, and diverging. Each chart type was used to visualize six attributes of data where half of the attributes have the characteristics of ‘lower better’ whereas the other half attributes are with ‘higher better.’ Thirty participants were asked to perform two types of comparison tasks: single-attribute and overall-attribute comparisons. We measured the completion time, error rate, and perceived difficulty of the comparison tasks. The results of the study suggest that, for overall-attribute comparisons, the inverting stacked bar chart was the most effective with regards to the completion time. The results also show that performing overall-attribute comparisons using the classical and diverging stacked bar charts required more time than performing single-attribute comparisons using these charts. Participants perceived the inverting and diverging stacked bar charts as easier-to-use than the classical stacked bar chart for overall-attribute comparisons. However, for single-attribute comparisons, all chart types delivered similar performance. We discuss how these findings can inform the better design of interactive stacked bar charts and visualization tools. Keywords: Stacked bar chart, Comparison task, User study, Multi-attribute data, Information visualizationhttp://www.sciencedirect.com/science/article/pii/S2468502X18300287 |
| spellingShingle | Indratmo Lee Howorko Joyce Maria Boedianto Ben Daniel The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons Visual Informatics |
| title | The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons |
| title_full | The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons |
| title_fullStr | The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons |
| title_full_unstemmed | The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons |
| title_short | The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons |
| title_sort | efficacy of stacked bar charts in supporting single attribute and overall attribute comparisons |
| url | http://www.sciencedirect.com/science/article/pii/S2468502X18300287 |
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