Applying Uncommon Visualizations to Government Dashboards

Puripant Ruchikachorn, Puripant Ruchikachorn

2021

Abstract

Many governments provide data dashboards to present the state of the countries or administrative activities. Their main target audience is typically the citizens but the dashboard design process is usually top-down and leads to formulaic results. Developing three data dashboard projects for the government of Thailand, we successfully applied two uncommon data visualizations, grid map and connected scatterplot, despite initial resistance from the government agencies. We documented the design process including feedback on the two visualizations and solutions to alleviate their concerns. Academic studies had little success in convincing stakeholders. In both visualizations, animations helped to frame the concept of the uncommon visualizations.

Paper Citation

in Harvard Style

Ruchikachorn P. (2021). Applying Uncommon Visualizations to Government Dashboards. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP; ISBN 978-989-758-488-6, SciTePress, pages 203-209. DOI: 10.5220/0010298102030209

in Bibtex Style

@conference{ivapp21,
author={Puripant Ruchikachorn},
title={Applying Uncommon Visualizations to Government Dashboards},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP},
year={2021},
pages={203-209},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010298102030209},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP
TI - Applying Uncommon Visualizations to Government Dashboards
SN - 978-989-758-488-6
AU - Ruchikachorn P.
PY - 2021
SP - 203
EP - 209
DO - 10.5220/0010298102030209
PB - SciTePress