CfP: Special Track on Simulation Visualization at ACM SIGSIM PADS

[Torsten Moeller]

Dear colleagues,

At the upcoming ACM SIGSIM International Conference on Principles of
Advanced Discrete Simulation (PADS) there will be a special track on

"Visualization for Communicating and Understanding Simulation Studies and
Results".

(see https://sigsim.acm.org/conf/pads/2026/blog/cfp/)

This track encourages submissions that focus on visualization and visual
analytics methods and tools for enhancing the communication and interpretation
of simulation results.

The conference invites submissions of both full papers (at most 10 pages, not
including references) as well as short papers (at most 4 pages, not including
references).

The deadlines are:

*) Submission Deadline: February 13, 2025
*) Notification of Acceptance: March 23, 2025

Papers selected by the program committee will be included in a special issue of
ACM Transactions on Modeling and Computer Simulation (TOMACS).

The conference will take place in Vienna, Jun 24-26, 2026.

For more information, please refer to the conference website:
https://sigsim.acm.org/conf/pads/2026/

The special track is designed to attract an interdisciplinary audience,
including visualization researchers and practitioners who are keen on
developing innovative techniques for interpreting and communicating complex
data, as well as members of the simulation community interested in leveraging
advanced visualization methods to enhance the analysis and presentation of
their simulation studies. The goal is to foster collaboration and knowledge
exchange between these communities to drive forward both fields.

Topics of interest include, but are not limited to:

*) Visualization for Decision Support: Design and development of visual tools
that enhance decision-making processes by effectively conveying simulation
outcomes

*) Comparative Visualization: Techniques for comparing multiple simulations or
datasets visually to identify patterns, differences, and trends

*) Uncertainty Visualization: Visual methods for representing and communicating
uncertainties inherent in simulation studies

*) Scalability in Visualization: Approaches for handling large-scale simulation
data in a visually effective manner

*) Storytelling and Narrative Visualization: Methods and approaches for
creating dynamic narratives around simulation studies

*) Immersive Analytics: Solutions that allow users to interact with and explore
simulation data in immersive environments

*) User-Centered Design: Creating visualization tools tailored to the needs of
diverse stakeholders, from modelers to decision-makers

*) Automated Visualization Pipelines: Methodologies for automating the
generation of insightful visualizations from simulation results

*) Machine Learning Integration: Visualization methods that incorporate machine
learning to automatically generate, optimize, or refine visual representations
of simulation data

Torsten + Markus