[Ieee_vis] CFP: IEEE Pacific Visualization 2016 Symposium

[Xiaoru Yuan]

*IEEE Pacific Visualization 2016 Symposium （*http://www.pvis.org）
*Call For Papers*

The 9th IEEE Pacific Visualization Symposium (PacificVis 2016) will be held
in Taipei, Taiwan from April 19 to 22, 2016. Visualization has become an
increasingly important research area due to its wide range of applications
in many disciplines. PacificVis is an IEEE sponsored international
visualization symposium held in the Asia-Pacific region, with the objective
to foster greater exchange between visualization researchers and
practitioners, and to draw more researchers in the Asia-Pacific region to
enter this rapidly growing area of research.

PacificVis is a unified visualization symposium, welcoming all areas of
visualization research such as: information, scientific, graph, security,
software and bio-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unpublished research and application papers in all areas of visualization.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 2016 will be published in the proceedings by
IEEE and will be also included in the IEEE Digital Library. Selected
research papers of outstanding quality will appear in IEEE Transactions of
Visualization and Computer Graphics.

*Important Dates*
- Abstract due: September 25, 2015
- Full paper due: October 2, 2015
- Reviews due: November 9, 2015
- 1st cycle notification:  November 23, 2015
- Revision: January 4, 2016
- 2nd cycle notification: January 25, 2016
- Camera ready paper due: Feb 5, 2016

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/ terrain visualization
- molecular, biomedical, bioinformatics and medical visualization
- text, documents and software visualization
- social, ambient and information sciences
- education and everyday visualization
- multimedia (image/video/music) visualization
- any other non-spatial data or spatial data that is visualized with a new
spatial mapping


*Data focused visualization research:*- high-dimensional data and
dimensionality reduction and data compression
- multidimensional 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 (e.g., social
sciences, biology, geography, software engineering, circuit design,
business intelligence)
- interfaces and interaction techniques for graph and network visualizations
- benchmarks and experimental analysis for graph visualization systems and
user interfaces

*Interaction focused visualization research:*
- icon- and glyph-based visualization
- focus + context techniques
- animation
- zooming and navigation
- linking + brushing
- 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
- cognitive studies on graph drawing 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
- validation and verification
- perception theory including such factors as color texture, scene, motion
perception, perceptual cognition


*System focused visualization research:*- novel algorithms and mathematics
- mobile and ubiquitous
- 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
- mathematical theories for visualization


*Hardware, Display and Interaction Technology:*- large and high-res 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*
Original unpublished papers of up to 8 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 (http://junctionpublishing.org/vgtc/Tasks/camera.html). DOC and
LaTeX templates are available. Reviewing will be double blind, please
remove all author and affiliation information from submissions and
supplemental files. Please 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.

Submission system : https://precisionconference.com/~vgtc

*Paper Types*
A VIS paper typically falls into one of five categories: technique, system,
design study, evaluation, or 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 more detailed
discussion on how to write a successful VIS paper.

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 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. For further suggestions, please review "How
(and How Not) to Write a Good Systems Paper" by Roy Levin and David Redell,
and "Empirical Methods in CS and AI" by Toby Walsh.

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 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.

Sincerely,

the IEEE Pacific Visualization 2016 Symposium co-chairs,
Chuck Hansen, University of Utah, USA
Xiaoru Yuan, Peking University, China
Ivan Viola, TU Wien, Austria
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