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arXiv · 2505.19101

Agentic Visualization: Extracting Agent-based Design Patterns from Visualization Systems

Vaishali Dhanoa·Anton Wolter·Gabriela Molina León·Hans-Jörg Schulz·Niklas Elmqvist
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Abstract

Autonomous agents powered by Large Language Models are transforming AI, creating an imperative for the visualization field to embrace agentic frameworks. However, our field's focus on a human in the sensemaking loop raises critical questions about autonomy, delegation, and coordination for such \textit{agentic visualization} that preserve human agency while amplifying analytical capabilities. This paper addresses these questions by reinterpreting existing visualization systems with semi-automated or fully automatic AI components through an agentic lens. Based on this analysis, we extract a collection of design patterns for agentic visualization, including agentic roles, communication and coordination. These patterns provide a foundation for future agentic visualization systems that effectively harness AI agents while maintaining human insight and control.

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Vaishali Dhanoa, Anton Wolter, Gabriela Molina León, Hans-Jörg Schulz, Niklas Elmqvist. 2025-05-25. Agentic Visualization: Extracting Agent-based Design Patterns from Visualization Systems. https://doi.org/10.1109/mcg.2025.3607741

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