Investigating time series visualisations to improve the user experience
- Submitting institution
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Heriot-Watt University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 10593778
- Type
- E - Conference contribution
- DOI
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10.1145/2858036.2858300
- Title of conference / published proceedings
- CHI'16: 2016 CHI Conference on Human Factors in Computing Systems Proceedings
- First page
- 5444
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- May
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Citation count
- 13
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents the first study to confirm that time series visualisations can be enhanced with interaction techniques without resulting in a significant loss of efficiency or accuracy. Existing visual analytics research focused only on the visual representation of data, while existing graphical perception studies were conducted only in static settings. Our rigorous study, conducted with multiple visual encodings, coordinate systems, and interaction techniques, settled this question. This paper was accepted for publication at ACM SIGCHI, the premier international conference on human-computer interaction.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
