Evaluating Line Chart Strategies for Mitigating Density of Temporal Data: The Impact on Trend, Prediction and Decision-Making

Rifta Ara Proma, Ghulam Jilani Quadri and Paul Rosen

In Proceedings of 20th International Symposium on Visual Computing 2025

Abstract

Overplotted line charts can obscure trends in temporal data and hinder prediction. We conduct a user study comparing three al- ternatives—aggregated, trellis, and spiral line charts against standard line charts on tasks involving trend identification, making predictions, and decision-making. We found aggregated charts performed similarly to standard charts and support more accurate trend recognition and predic- tion; trellis and spiral charts generally lag. We also examined the impact on decision-making via a trust game. The results showed similar trust in standard and aggregated charts, varied trust in spiral charts, and a lean toward distrust in trellis charts. These findings provide guidance for practitioners choosing visualization strategies for dense temporal data.

Citation

@misc{proma2025evaluatinglinechartstrategies,
      title={Evaluating Line Chart Strategies for Mitigating Density of Temporal Data: The Impact on Trend, Prediction, and Decision-Making}, 
      author={Rifat Ara Proma and Ghulam Jilani Quadri and Paul Rosen},
      year={2025},
      eprint={2510.11912},
      archivePrefix={arXiv},
      primaryClass={cs.HC},
      url={https://arxiv.org/abs/2510.11912}, 
}