[Infovis] IEEE PacificVis 2021 Call for Papers

[Chaoli Wang]

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 Call for Papers: 14th IEEE Pacific Visualization Symposium (PacificVis
2021)
                            APRIL 19-22, 2021
                        Pan Pacific, TIANJIN, China
                             http://pvis.org/
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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
specific applications such as (but not limited to) security, software, and
biological visualization. Authors are invited to submit original and
unpublished research and application papers in all areas of visualization.
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 papers accepted by
IEEE Pacific Visualization 2021 will be published by IEEE and will also be
included in the IEEE Digital Library. Selected papers will be published
directly in IEEE Transactions on Visualization and Computer Graphics (TVCG).


Important Dates
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Abstract due            : Sep. 25, 2020
Full paper due          : Oct. 2,  2020
Reviews due             : Nov. 13, 2020
1st cycle notification  : Nov. 27, 2020
Revision due            : Dec. 18, 2020
2nd cycle notification  : Jan. 11, 2021
Camera ready paper due  : Jan. 21, 2021

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


Topics
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Suggested topics include, but are not limited to:

Visualization Application Areas:
* 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
* Text, Document, and Software Visualization
* Social and Information Sciences
* Education and Everyday Visualization
* Multimedia (Image/Video/Music) Visualization

Data-focused Visualization Research:
* High-dimensional Data, Dimensionality Reduction, and Data Compression
* Multi-field, Multi-modal, Multi-resolution, and Multi-variate 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 (Petabytes, ...)

Technique-focused Visualization Research:
* Volume Modeling and Rendering
* Extraction of Surfaces
* Topology-based and Geometry-based Techniques
* Glyph-based Techniques
* Integrating Spatial and Non-spatial Data Visualization
* Machine Learning Approaches

Graph and Network Visualization Research:
* Design and Experimentation of Graph Drawing Algorithms
* Techniques, Interfaces, and Interaction Methods for Graphs, Trees, and
Other Relational Data
* Visualization of Graphs and Networks in Application Areas
* Interfaces and Interaction Techniques for Graph and Network Visualizations
* Benchmarks and Experimental Analysis for Graph Visualization Systems

Interaction-focused Visualization Research:
* 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

Empirical and Comprehension-focused Visualization Research:
* 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
* Metrics and Benchmarks
* Evaluations of All Types: Qualitative, Quantitative, Laboratory, Field,
and Usability Studies
* Use of Eye Tracking and Other Biometric Measures

System-focused Visualization Research:
* Novel Algorithms and Mathematics
* Taxonomies and Models
* Methodologies, Discussions, and Frameworks
* Visual Design, Visualization System, and Toolkit Design
* Data Warehousing, Database Visualization, and Data Mining
* Collaborative and Distributed Visualization

Hardware, Display, and Interaction Technology:
* 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


Submission
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Papers are to be submitted online through the new Precision Conference
System (https://new.precisionconference.com/user/login?society=vgtc) at the
PacificVis 2021 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 (https://pacificvis.github.io/). 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.


Papers Chairs
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Nan Cao
Tongji University, China

Holger Theisel
University of Magdeburg, Germany

Chaoli Wang
University of Notre Dame, USA


Email: pvis_papers at pvis.org


Paper Types
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A visualization research paper typically falls into one of five categories:
technique, system, application/design study, evaluation, or theory/model.
We briefly discuss these categories below. Although your main paper type
has to be specified during the paper submission process, papers can include
elements of more than one of these categories. Please see “Process and
Pitfalls in Writing Information Visualization Research Papers” by Tamara
Munzner for a more detailed discussion.

*Technique papers* introduce novel techniques or algorithms that have not
previously appeared in the literature, or that significantly extend known
techniques or algorithms, for example, by scaling to datasets of much
larger size than before or by generalizing a technique to a larger class of
uses. The technique or algorithm description provided in the paper should
be complete enough that a competent graduate student in visualization could
implement the work, and the authors should create a prototype
implementation of the methods. Relevant previous work must be referenced,
and the advantage of the new methods over it should be clearly
demonstrated. There should be a discussion of the tasks and datasets for
which this new method is appropriate, and its limitations. Evaluation
through informal or formal user studies, or other methods, will often serve
to strengthen the paper, but are not mandatory.

*System papers* present a blend of algorithms, technical requirements, user
requirements, and design that solves a major problem. The system that is
described is both novel and important, and has been implemented. The
rationale for significant design decisions is provided, and the system is
compared to documented, best-of-breed systems already in use. The
comparison includes a specific discussion of how the described system
differs from and is, in some significant respects, superior to those
systems. For example, the described system may offer substantial
advancements in the performance or usability of visualization systems or
novel capabilities. Every effort should be made to eliminate external
factors (such as advances in processor performance, memory sizes, or
operating system features) that would affect this comparison.

*Application/design study papers* explore the choices made when applying
visualization and visual analytics techniques in an application area, for
example relating the visual encodings and interaction techniques to the
requirements of the target task. Similarly, application/design study papers
have been the norm when researchers describe the use of visualization
techniques to glean insights from problems in engineering and science.
Although a significant amount of application domain background information
can be useful to provide a framing context in which to discuss the
specifics of the target task, the primary focus of the case study must be
the visualization content. The results of the application/design study,
including insights generated in the application domain, should be clearly
conveyed. Describing new techniques and algorithms developed to solve the
target problem will strengthen a design study paper, but the requirements
for novelty are less stringent than in a technique paper. Where necessary,
the identification of the underlying parametric space and its efficient
search must be aptly described. The work will be judged by the design
lessons learned or insights gleaned, on which future contributors can
build. We invite submissions on any application area.

*Evaluation papers* explore the usage of visualization and visual analytics
by human users, and typically present an empirical study of visualization
techniques or systems. Authors are not necessarily expected to implement
the systems used in these studies themselves; the research contribution
will be judged on the validity and importance of the experimental results
as opposed to the novelty of the systems or techniques under study. The
conference committee appreciates the difficulty and importance of designing
and performing rigorous experiments, including the definition of
appropriate hypotheses, tasks, data sets, selection of subjects,
measurement, validation, and conclusions. The goal of such efforts should
be to move from mere description of experiments, toward prediction and
explanation. We do suggest that potential authors who have not had formal
training in the design of experiments involving human subjects may wish to
partner with a colleague from an area such as psychology or human-computer
interaction who has experience with designing rigorous experimental
protocols and statistical analysis of the resulting data. Other novel forms
of evaluation are also encouraged.

*Theory/model papers* present new interpretations of the foundational
theory of visualization and visual analytics. Implementations are usually
not relevant for papers in this category. Papers should focus on basic
advancement in our understanding of how visualization techniques complement
and exploit properties of human vision and cognition.

For more information and updates, please visit: http://pvis.org/