# DIVI: Dynamically Interactive Visualization

arXiv: https://arxiv.org/abs/2310.17814 · HTML: https://mlsanity.com/paper/2310.17814/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Oct 2023.

## Built on by (most cited first, 5 of 5)

- [From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems](https://mlsanity.com/paper/2408.03876/) (2024)
- [DATAWEAVER: Authoring Data-Driven Narratives through the Integrated Composition of Visualization and Text](https://mlsanity.com/paper/2503.22946/) (2025)
- [Challenges & Opportunities with LLM-Assisted Visualization Retargeting](https://mlsanity.com/paper/2507.01436/) (2025)
- [From Static to Interactive: Authoring Interactive Visualizations via Natural Language](https://mlsanity.com/paper/2601.17736/) (2026)
- [Chart2SVG: Editable SVG Generation from Raster Chart Images](https://mlsanity.com/paper/2608.26544/) (2026)

## Abstract (arXiv)

Dynamically Interactive Visualization (DIVI) is a novel approach for orchestrating interactions within and across static visualizations. DIVI deconstructs Scalable Vector Graphics charts at runtime to infer content and coordinate user input, decoupling interaction from specification logic. This decoupling allows interactions to extend and compose freely across different tools, chart types, and analysis goals. DIVI exploits positional relations of marks to detect chart components such as axes and legends, reconstruct scales and view encodings, and infer data fields. DIVI then enumerates candidate transformations across inferred data to perform linking between views. To support dynamic interaction without prior specification, we introduce a taxonomy that formalizes the space of standard interactions by chart element, interaction type, and input event. We demonstrate DIVI's usefulness for rapid data exploration and analysis through a usability study with 13 participants and a diverse gallery of dynamically interactive visualizations, including single chart, multi-view, and cross-tool configurations.