A Comparative Study of Visualizations for Multiple Time Series

Max Franke, Moritz Knabben, Julian Lang, Steffen Koch, Tanja Blascheck

2022

Abstract

Different visualization techniques are suited for visualizing data of multiple time series. Choosing an appropriate visualization technique depends on data characteristics and tasks. Previous work has explored such combinations of data and visualization techniques in lab-based studies to find the most suited technique for a task. Using these previous findings, we performed an online study with 51 participants, during which we compare line charts, stream graphs, and aligned area charts based on completion time and accuracy regarding three common discrimination tasks. Our online study includes a novel combination of visualization techniques for time-dependent data and indicates that there are certain differences and trends regarding the suitability of the visualizations for different tasks. At the same time, we can confirm results presented in previous work.

Paper Citation

in Harvard Style

Franke M., Knabben M., Lang J., Koch S. and Blascheck T. (2022). A Comparative Study of Visualizations for Multiple Time Series. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 3: IVAPP; ISBN 978-989-758-555-5, SciTePress, pages 103-112. DOI: 10.5220/0010761700003124

in Bibtex Style

@conference{ivapp22,
author={Max Franke and Moritz Knabben and Julian Lang and Steffen Koch and Tanja Blascheck},
title={A Comparative Study of Visualizations for Multiple Time Series},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 3: IVAPP},
year={2022},
pages={103-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010761700003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 3: IVAPP
TI - A Comparative Study of Visualizations for Multiple Time Series
SN - 978-989-758-555-5
AU - Franke M.
AU - Knabben M.
AU - Lang J.
AU - Koch S.
AU - Blascheck T.
PY - 2022
SP - 103
EP - 112
DO - 10.5220/0010761700003124
PB - SciTePress