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Paper Topics

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


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