# Calliope: Automatic Visual Data Story Generation from a Spreadsheet

arXiv: https://arxiv.org/abs/2010.09975 · HTML: https://mlsanity.com/paper/2010.09975/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Oct 2020.

## Built on by (most cited first, 30 of 30)

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- [Chart Question Answering: State of the Art and Future Directions](https://mlsanity.com/paper/2205.03966/) (2022)
- [HAIChart: Human and AI Paired Visualization System](https://mlsanity.com/paper/2406.11033/) (2024)
- [DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts](https://mlsanity.com/paper/2408.05346/) (2024)
- [DataTales: Investigating the use of Large Language Models for Authoring Data-Driven Articles](https://mlsanity.com/paper/2308.04076/) (2023)
- [Generative AI for Visualization: State of the Art and Future Directions](https://mlsanity.com/paper/2404.18144/) (2024)
- [Telling Stories from Computational Notebooks: AI-Assisted Presentation Slides Creation for Presenting Data Science Work](https://mlsanity.com/paper/2203.11085/) (2022)
- [Where Are We So Far? Understanding Data Storytelling Tools from the Perspective of Human-AI Collaboration](https://mlsanity.com/paper/2309.15723/) (2023)
- [Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling](https://mlsanity.com/paper/2304.08366/) (2023)
- [Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions](https://mlsanity.com/paper/2409.19747/) (2024)
- [DATAWEAVER: Authoring Data-Driven Narratives through the Integrated Composition of Visualization and Text](https://mlsanity.com/paper/2503.22946/) (2025)
- [DataTales: A Benchmark for Real-World Intelligent Data Narration](https://mlsanity.com/paper/2410.17859/) (2024)
- [LLM-Assisted Visual Analytics: Opportunities and Challenges](https://mlsanity.com/paper/2409.02691/) (2024)
- [ReSpark: Leveraging Previous Data Reports as References to Generate New Reports with LLMs](https://mlsanity.com/paper/2502.02329/) (2025)
- [Infogen: Generating Complex Statistical Infographics from Documents](https://mlsanity.com/paper/2507.20046/) (2025)
- [Gen4DS: Workshop on Data Storytelling in an Era of Generative AI](https://mlsanity.com/paper/2404.01622/) (2024)
- [MDSF: Context-Aware Multi-Dimensional Data Storytelling Framework based on Large language Model](https://mlsanity.com/paper/2501.01014/) (2025)
- [FactFlow: Automatic Fact Sheet Generation and Customization from Tabular Dataset via AI Chain Design & Implementation](https://mlsanity.com/paper/2502.17909/) (2025)
- [Reflection on Data Storytelling Tools in the Generative AI Era from the Human-AI Collaboration Perspective](https://mlsanity.com/paper/2503.02631/) (2025)
- [DashChat: Interactive Authoring of Performance Dashboard Design Prototypes through Conversation with LLM-Powered Agent](https://mlsanity.com/paper/2504.12865/) (2025)
- [DATAREEL: Automated Data-Driven Video Story Generation with Animations](https://mlsanity.com/paper/2604.25220/) (2026)
- [Feature-Action Design Patterns for Storytelling Visualizations with Time Series Data](https://mlsanity.com/paper/2402.03116/) (2024)
- [DataScout: Automatic Data Fact Retrieval for Statement Augmentation with an LLM-Based Agent](https://mlsanity.com/paper/2504.17334/) (2025)
- [NOVAID: Natural-language Observability Visualization Assistant for ITOps Dashboard Widget Generation](https://mlsanity.com/paper/2601.11531/) (2025)
- [Crystalis: Progressive Nucleation and Semantic Annealing for Coordinated Multi-View Visualization Generation](https://mlsanity.com/paper/2607.24766/) (2026)
- [InsightChain: Optimized Chain-of-Insight Analytics for LLM-driven Data Visualization](https://mlsanity.com/paper/2609.06438/) (2026)
- [InfoAgent: Traceable Generation and Repair of Evidence-Grounded Infographics](https://mlsanity.com/paper/2609.39380/) (2026)
- [Intent Graph: Navigating the Analytical Reasoning Space for Exploratory Data Analysis](https://mlsanity.com/paper/2610.11025/) (2026)

## Abstract (arXiv)

Visual data stories shown in the form of narrative visualizations such as a poster or a data video, are frequently used in data-oriented storytelling to facilitate the understanding and memorization of the story content. Although useful, technique barriers, such as data analysis, visualization, and scripting, make the generation of a visual data story difficult. Existing authoring tools rely on users' skills and experiences, which are usually inefficient and still difficult. In this paper, we introduce a novel visual data story generating system, Calliope, which creates visual data stories from an input spreadsheet through an automatic process and facilities the easy revision of the generated story based on an online story editor. Particularly, Calliope incorporates a new logic-oriented Monte Carlo tree search algorithm that explores the data space given by the input spreadsheet to progressively generate story pieces (i.e., data facts) and organize them in a logical order. The importance of data facts is measured based on information theory, and each data fact is visualized in a chart and captioned by an automatically generated description. We evaluate the proposed technique through three example stories, two controlled experiments, and a series of interviews with 10 domain experts. Our evaluation shows that Calliope is beneficial to efficient visual data story generation.