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 Authors are invited to submit original and unpublished research and application papers in all areas of visualization.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

	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.

Submission

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.

Chairs

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

Contact

Email: pvis_papers@pvis.org