CFP - Full Papers

CFP - Full Papers

PacificVis is a unified visualization symposium, welcoming all areas of visualization research such as information visualization, scientific visualization, graph and network visualization, visual analytics, and visualization applications in domains such as (but not limited to) biological sciences, education, machine learning, physical sciences, security, and social science. Authors are invited to submit original and unpublished research and application papers in all areas of visualization. PacificVis 2022 will be held in Tsukuba, Japan on April 11-14, 2022. We encourage papers in any new, novel, and exciting research area that pertains to visualization.

All submitted papers will go through a two-stage review process to guarantee the publication of high-quality papers. All accepted papers will be presented orally at the conference and will also be published by IEEE and included in the IEEE Digital Library. Selected papers will be published directly in IEEE Transactions on Visualization and Computer Graphics (TVCG).

Important Dates

Abstract due October 15, 2021
Full paper due October 22, 2021
1st cycle notification December 17, 2021
Revision due January 14, 2022
2nd cycle notification February 11, 2022
Camera ready paper due February 18, 2022

All deadlines are due at 9:00 pm Pacific Time (PDT/PST).

Paper Types and Topics

Suggested paper types and the corresponding topics include, but are not limited to:

Technique Paper

novel algorithms, visual encoding methods, and/or interaction techniques for data analysis, exploration, or communication. All sub-areas of data visualization and visual analytics are welcomed, including high-dimensional, time-series, spatial, geographic, text, hierarchical, and network data. Techniques may be specialized for specific devices or form-factors (e.g., mobile or wall-scale visualization). More topics in this category include but 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, Multi-modal, 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 and Rendering Techniques
  • Volume Modeling and Rendering
  • Extraction of Surfaces
  • Topology-based and Geometry-based Techniques
  • Glyph-based Techniques
  • Integrating Spatial and Non-spatial Data Visualization
Interaction Techniques for Supporting Data Analysis and Exploration
  • Icon- and Glyph-based Visualization
  • Focus + Context Techniques
  • Animation
  • Zooming and Navigation
  • Brushing + Linking
  • Coordinated Multiple Views
  • View-dependent Visualization
  • Data Labeling, Editing, and Annotation
  • Collaborative, Co-located, and Distributed Visualization
  • Manipulation and Deformation
  • Visual Data Mining and Visual Knowledge Discovery
Hardware, Display, and Interaction Technologies for Visualization
  • Large and High-resolution Displays
  • Stereo Displays
  • Mobile and Ubiquitous Environments
  • Immersive and Virtual Environments
  • Multimodal Input (Touch, Haptics, Voice, etc.)
  • Hardware Acceleration
  • GPUs and Multi-core Architectures
  • CPU and GPU Clusters
  • Distributed Systems, Grid, and Cloud Environments
  • Volume Graphics Hardware

Systems Paper

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. More topics in this category include but 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 Paper

novel use of visualization to address problems in an application domain, including accounts of innovative system design, deployment and impact. We welcome diverse application areas, including the physical sciences, life sciences, social sciences, engineering, arts, sports, and humanities. More topics in this category include but 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
  • Social and Information Sciences
  • Education and Everyday Visualization
  • Multimedia (Image/Video/Music) Visualization

Evaluation & Empirical Research Paper

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. More topics in this category include but not limited to:

  • Evaluations of All Types: Qualitative, Quantitative, Laboratory, Field, and Usability Studies
  • Metrics and Benchmarks
  • Use of Eye Tracking and Other Biometric Measures

Theory Paper

models of visual encoding, interaction, and/or analysis tasks; implications from theories of perception, cognition, design, and/or aesthetics; methods for automated design or visualization recommendation. More topics in this category include but not limited to:

  • Visual Design and Aesthetics
  • Illustrative Visualization
  • Cognition and Perception Issues
  • User Studies on Visualization Readability and User Interaction
  • Presentation, Dissemination, and Storytelling
  • Design Studies, Case Studies, and Focus Groups
  • Task and Requirements Analysis

For a wider range of paper types, please see “Broadening Intellectual Diversity in Visualization Research Papers” by B. Lee et al.


Papers are to be submitted online through the new Precision Conference System at the PacificVis 2022 Papers track.

Original, unpublished papers of up to ten (10) pages (two-column, single-spaced, 9 point font, including figures, tables, and references) are invited. Manuscripts must be written in English and follow the formatting guidelines. It is recommended (but not mandatory) to submit an anonymized version of your manuscript for double-blind review - in this case, please remove all author and affiliation information from submissions and supplemental files as well as substitute your paper’s ID number for the author name. Papers should be submitted electronically in Adobe PDF format. Please provide supplemental videos in QuickTime MPEG-4 or DivX version 5, and use TIFF, JPEG, or PNG for supplemental images.


Nan Cao
Tongji University, China

Timo Ropinski
Ulm University, Germany

Jian Zhao
University of Waterloo, Canada

PC Members

Pengcheng An University of Waterloo
Stefan Bruckner University of Bergen
Guoning Chen University of Houston
Qing Chen Tongji University
Siming Chen Fraunhofer IAIS
Zhutian Chen Harvard University
Weiwei Cui Microsoft Research Asia
Walter Didimo University of Perugia
Fan Du Adobe Research
Soumya Dutta Los Alamos National Lab
Issei Fujishiro Keio University
Christoph Garth Technische Universität Kaiserslautern
Hanqi Guo Argonne National Laboratory
Shunan Guo Adobe Research
Markus Hadwiger KAUST
Wenbin He Bosch Research North America
Seokhee Hong  
Takayuki Itoh Ochanomizu University
Yun Jang Sejong University
Sungahn Ko UNIST
Stephen Kobourov University of Arizona
Koji Koyamada Kyoto University
Michael Krone University of Tübingen
Bum Chul Kwon IBM Research
Oh-Hyun Kwon Apple
Giuseppe Liotta University of Perugia
Zhicheng Liu University of Maryland
Aidong Lu University of North Carolina at Charlotte
Min Lu Shenzhen University
Kwan-Liu Ma University of California at Davis
Kresimir Matkovic VRVis Research Center
Paul Rosen University of South Florida
Thomas Schultz University of Bonn
Yang Shi Tongji University
Bettina Speckmann Eindhoven University of Technology
Maoyuan Sun Northern Illinois University
Wenbo Tao MIT
Bei Wang Scientific Computing and Imaging Institute
Chaoli Wang University of Notre Dame
Junpeng Wang Visa Research
Yong Wang Singapore Management University
Yun Wang Microsoft Research Asia
Yunhai Wang Shandong University
Tino Weinkauf KTH Royal Institute of Technology
Hsiang-Yun Wu St. Pölten University of Applied Sciences
Yingcai Wu Zhejiang University
Jiazhi Xia Central South University
Ke Xu Huawei Technologies Co. Ltd
Panpan Xu Amazon AWS Machine Learning
Hsu-Chun Yen National Taiwan University
Hongfeng Yu UNL
Yue Zhang Oregon State University
Ying Zhao Central South University
Zichun Zhong Wayne State University