# Task-Oriented Optimal Sequencing of Visualization Charts

arXiv: https://arxiv.org/abs/1908.02502 · HTML: https://mlsanity.com/paper/1908.02502/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Aug 2019.

## Built on by (most cited first, 4 of 4)

- [DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts](https://mlsanity.com/paper/2408.05346/) (2024)
- [Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Way](https://mlsanity.com/paper/2408.16119/) (2024)
- [DATAREEL: Automated Data-Driven Video Story Generation with Animations](https://mlsanity.com/paper/2604.25220/) (2026)
- [DataScout: Automatic Data Fact Retrieval for Statement Augmentation with an LLM-Based Agent](https://mlsanity.com/paper/2504.17334/) (2025)

## Abstract (arXiv)

A chart sequence is used to describe a series of visualization charts generated in the exploratory analysis by data analysts. It provides information details in each chart as well as a logical relationship among charts. While existing research targets on generating chart sequences that match human's perceptions, little attention has been paid to formulate task-oriented connections between charts in a chart design space. We present a novel chart sequencing method based on reinforcement learning to capture the connections between charts in the context of three major analysis tasks, including correlation analysis, anomaly detection, and cluster analysis. The proposed method formulates a chart sequencing procedure as an optimization problem, which seeks an optimal policy to sequencing charts for the specific analysis task. In our method, a novel reward function is introduced, which takes both the analysis task and the factor of human cognition into consideration. We conducted one case study and two user studies to evaluate the effectiveness of our method under the application scenarios of visualization demonstration, sequencing charts for reasoning analysis results, and making a chart design choice. The study results showed the power of our method.