As a unified visualization conference, IEEE PacificVis welcomes novel intellectual contributions from all areas of visualization research. This document provides examples of possible contributions. However, we welcome all contributions to visualization; successful papers may combine or go beyond these contribution topics.

Visualization Techniques

Technique contributions mainly involve novel algorithms, visual encoding methods, and/or interaction techniques for data analysis, exploration, or communication. Techniques may be specialized for specific devices or form-factors (e.g., mobile or wall-scale visualization). Topics include but are not limited to:

Visualization Techniques for a Broad Range of Data Types:

High-dimensional Data, Dimensionality Reduction, and Data Compression
Graphs and Networks
Text and Documents
Multi-field, Multimodal, Multi-resolution, and Multivariate Data
Causality and Uncertainty Data
Time Series, Time-varying, Streaming, and Flow Data
Scalar, Vector, and Tensor Fields
Regular and Unstructured Grids
Point-based Data
Large-scale Data

Visual Encoding, Feature Extraction, and Rendering Techniques:

Volume Modeling and Rendering
Visual Design and Aesthetics
Illustrative Visualization
Extraction of Surfaces
Topology-based and Geometry-based Techniques
Icon- and Glyph-based Techniques
Integrating Spatial and Non-spatial Data Visualization

Interaction Techniques for Supporting Data Analysis and Exploration:

Animation
Coordinated Multiple Views and Brushing & Linking
Data Labeling, Editing, and Annotation
Collaborative, Co-located, and Distributed Visualization
Manipulation and Deformation
Visual Data Mining and Visual Knowledge Discovery
Data Storytelling
Natural Language, Gesture, and Multimodal Interaction

Hardware, Display, and Interaction Technologies for Visualization:

Large and High-resolution Displays
Stereo Displays
Mobile and Ubiquitous Environments
Situated and Immersive Analytics
Data physicalization
Multimodal Input (Touch, Haptics, Voice, etc.)
Hardware Architectures for Visualization

VIS x AI:

Visualization for AI Explainability, Security, and Privacy
Visualization for AI Data Collection, Training, and Deployment
AI for Visualization Generation and Data Analysis
Machine Learning Assisted Visualization
LLMs and Generative Models

Systems

System contributions include new software frameworks, languages, or tools for visualization; systems for large-scale visualization; integrated graphical systems for visual analysis or interactive machine learning; collaborative and web-scale visualization systems. Topics in this category include but are not limited to:

System Taxonomies and Design Patterns
Methodologies, Discussions, and Frameworks
Visual Analysis Systems, and Visualization Toolkits
Visual Data Warehousing, Database Visualization, and Visual Data Mining Systems
Collaborative and Distributed Visualization Systems

Applications & Design Studies

These contributions involve the novel use of visualization to address problems in an application domain, including accounts of innovative system design, deployment and impact. Topics in this category include but are not limited to:

Statistical Graphics and Mathematics
Financial, Security, and Business Visualization
Physical Sciences and Engineering
Earth, Space, and Environmental Sciences
Geographic, Geospatial, and Terrain Visualization
Molecular, Biomedical, Bioinformatics, and Medical Visualization
Software Visualization
Machine Learning Visualization
Social and Information Sciences
Education and Everyday Visualization
Multimedia (Image/Video/Music) Visualization

Evaluation & Empirical Research

Evaluation contributions include comparative evaluation of competing visualization approaches; controlled experiments to inform visualization best practices; longitudinal and qualitative studies to understand user needs, visualization adoption, and use. Topics in this category include but are not limited to:

Evaluations
Qualitative evaluation
Quantitative evaluation
Laboratory studies
Field studies
Usability studies
Longitudinal studies
Metrics and Benchmarks
Use of Eye Tracking and Other Biometric Measures

Visualization Theory

Theoretical contributions focus on fundamental questions related to understanding, assessing, categorizing, or formalizing visual data analysis. Topics in this category include but are not limited to:

Cognition and Perception
Frameworks and Models for Visualization or Interaction
New methodologies for visualization research and design
Visualization guidelines and heuristics
Taxonomies and ontologies
Mathematical abstraction