Call for Contributions

Uncertainty visualization has been recognized as one of the grand research challenges that must be addressed for trusted scientific discovery and decision-making. Visualization of uncertainty, however, is nontrivial given many difficult relevant challenges, including uncertainty modeling, computation, communication, perception, cognition, and decision-making under uncertainty. Furthermore, widespread use of artificial intelligence (AI) technologies across scientific workflows makes visualization and analysis of uncertainty even more challenging. Our workshop will provide a platform that would foster interdisciplinary interaction and dissemination of work, which will be critical to identifying research priorities for tackling theoritical and application-specific uncertainty visualization challenges that are currently obstacles to scientific progress.

The workshop welcomes researchers with expertise in diverse areas, including but not limited to computation, visualization, machine learning (ML), artificial intelligence (AI), perception, cognition, application science, mathematics, applied math, to submit short/full papers on effective analysis and decision-making under uncertainty for data and AI. This call is flexible to cover a broad range of studies in uncertainty analysis, including novel research contributions, domain-specific or general requirements for successful uncertainty analysis, obstacles to understanding data uncertainty presented through use cases, and successful uncertainty visualization workflows for robust solutions.

The workshop welcomes submissions of short and full papers. The accepted papers will be published in IEEE proceedings and invited for presentation during the workshop.

Scope

Relevant topics include (but are not limited to):

• Uncertainty Propagation: Techniques to effectively model data uncertainty, Statistical/Probabilistic techniques to propagate uncertainty through complex data processing pipelines, Uncertainty propagation techniques in application domain, including but not limited to climate science, quantum computing, energy science, and material science.
• Uncertainty Communication: Techniques to convey uncertainty in 2D/3D/high-dimensional (scientific or information) data, Effective ways to educate non-experts and scientific users about uncertainty visualization, Visualization tools or software to communicate uncertainty.
• AI and Uncertainty Visualization: Techniques to visualize uncertainty in AI models for explainability, AI techniques for propagation and visualization of uncertainty in data, and AI for generalization of uncertainty visualization across application domains.
• Decision-Making Under Uncertainty: Obstacles to effective decision-making under uncertainty, User studies to evaluate the influence of uncertainty visualization on decision-making, and AI and statistical techniques for robust decision-making under uncertainty.

Important Dates

• Deadline for submission: July 10, 2025
• Author notification: August 7, 2025
• Camera-ready papers due: August 18, 2025
• IEEE VIS: November 2-7, 2025

All deadlines are in Anywhere on Earth (AoE) time zone.