# The State of the Art in Creating Visualization Corpora for Automated Chart Analysis

arXiv: https://arxiv.org/abs/2305.14525 · HTML: https://mlsanity.com/paper/2305.14525/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 May 2023.

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

- [Generative AI for Visualization: State of the Art and Future Directions](https://mlsanity.com/paper/2404.18144/) (2024)
- [Mystique: Deconstructing SVG Charts for Layout Reuse](https://mlsanity.com/paper/2307.13567/) (2023)
- [V-RECS, a Low-Cost LLM4VIS Recommender with Explanations, Captioning and Suggestions](https://mlsanity.com/paper/2406.15259/) (2024)
- [ChartKG: A Knowledge-Graph-Based Representation for Chart Images](https://mlsanity.com/paper/2410.09761/) (2024)

## Abstract (arXiv)

We present a state-of-the-art report on visualization corpora in automated chart analysis research. We survey 56 papers that created or used a visualization corpus as the input of their research techniques or systems. Based on a multi-level task taxonomy that identifies the goal, method, and outputs of automated chart analysis, we examine the property space of existing chart corpora along five dimensions: format, scope, collection method, annotations, and diversity. Through the survey, we summarize common patterns and practices of creating chart corpora, identify research gaps and opportunities, and discuss the desired properties of future benchmark corpora and the required tools to create them.