Vaishali DhanoaORCID iD, Anton WolterORCID iD, Gabriela Molina León, Hans-Jörg Schulz, Niklas ElmqvistORCID iD
Agentic Visualization: Extracting Agent-Based Design Patterns From Visualization Systems
IEEE Computer Graphics and Applications, 45(6):89-100, November 2025.

Information

  • Publication Type: Journal Paper (without talk)
  • Workgroup(s)/Project(s):
  • Date: November 2025
  • DOI: 10.1109/MCG.2025.3607741
  • ISSN: 1558-1756
  • Journal: IEEE Computer Graphics and Applications
  • Number: 6
  • Pages: 12
  • Volume: 45
  • Publisher: IEEE COMPUTER SOC
  • Pages: 89 – 100
  • Keywords: agents, visualization, design patterns

Abstract

Autonomous agents powered by large language models are transforming artificial intelligence (AI), creating an imperative for the visualization area. However, our field's focus on a human in the sensemaking loop raises critical questions about autonomy, delegation, and coordination for such agentic visualization that preserve human agency while amplifying analytical capabilities. This article addresses these questions by reinterpreting existing visualization systems with semiautomated 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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BibTeX

@article{dhanoa-2025-ave,
  title =      "Agentic Visualization: Extracting Agent-Based Design
               Patterns From Visualization Systems",
  author =     "Vaishali Dhanoa and Anton Wolter and Gabriela Molina
               Le\'{o}n and Hans-J\"{o}rg Schulz and Niklas Elmqvist",
  year =       "2025",
  abstract =   "Autonomous agents powered by large language models are
               transforming artificial intelligence (AI), creating an
               imperative for the visualization area. However, our field's
               focus on a human in the sensemaking loop raises critical
               questions about autonomy, delegation, and coordination for
               such agentic visualization that preserve human agency while
               amplifying analytical capabilities. This article addresses
               these questions by reinterpreting existing visualization
               systems with semiautomated 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.",
  month =      nov,
  doi =        "10.1109/MCG.2025.3607741",
  issn =       "1558-1756",
  journal =    "IEEE Computer Graphics and Applications",
  number =     "6",
  pages =      "12",
  volume =     "45",
  publisher =  "IEEE COMPUTER SOC",
  pages =      "89--100",
  keywords =   "agents, visualization, design patterns",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2025/dhanoa-2025-ave/",
}