Welcome

The 11th Pacific Visualization Symposium (PacificVis 2018) will be held in Kobe, Japan during April 10 to 13, 2018. Visualization has become an increasingly important research area due to its wide range of applications in many disciplines. PacificVis conference series has been an IEEE sponsored international visualization symposium held in the Asia-Pacific region. Its 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 visualization, scientific visualization, graph and network visualization, visual analytics, and specific applications such as (but not limited to) 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 Authors are invited to submit original and unpublished research and application papers in all areas of visualization.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. As in 2016 and 2017, selected papers will be published directly in IEEE Transactions on Visualization and Computer Graphics (TVCG).

http://pvis.org/

News

Important Dates

Full Papers

Abstract due Sep. 22, 2017
Full paper due Sep. 29, 2017
Reviews due Nov. 5, 2017
1st cycle notification Nov. 20, 2017
Revision due Jan. 5, 2018
2nd cycle notification Jan. 22, 2018
Camera ready paper due Feb. 2, 2018

Call for Papers

Full Papers

IMPORTANT DATES

Abstract due Sep. 22, 2017
Full paper due Sep. 29, 2017
Reviews due Nov. 5, 2017
1st cycle notification Nov. 20, 2017
Revision due Jan. 5, 2018
2nd cycle notification Jan. 22, 2018
Camera ready paper due Feb. 2, 2018

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

TOPICS

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 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 (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
  • Use Of Eye Tracking And Other Biometric Measures
  • 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 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. 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

Note: Formatting guidelines are under preparation. For the moment, please refer to the preparation guidelines for PacificVis 2017.

PAPERS CHAIRS

Email: pvis_papers(at)pvis.org

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.

PacificVAST 2018 Call for Papers

PacificVAST 2018 is an international workshop collocated with PacificVis 2018. In PacificVAST, participants share their state-of-the-art research results and fresh perspectives on visual analytics. Visual analytics is a discipline concerned with science and technology for analytical reasoning supported by interactive visual interfaces. Most papers presented in PacificVAST are distinguished from traditional visualization papers in that they harmoniously integrate interactive visual interfaces with analytical techniques from statistics, data mining, or machine learning fields to help analyze overwhelming amounts of disparate, conflicting, and dynamic information.

All aspects of visual analytics are covered in PacificVAST including, but not limited to the following topics:

The science of analytical reasoning
Visually enabled tools to support (collaborative) analytic reasoning about complex and dynamic problems Scalable visual analytic techniques
Visual representations and interaction techniques
  • Theories and techniques of visual representations based on cognitive and perceptual principles that can be deployed through engineered, reusable components
  • Novel visual paradigms that support the (collaborative) analytical reasoning process
  • Theories and techniques of user interactions that support the analytical reasoning process
Data representations, transformations, and integrations
  • Theory and practice for transforming data into new scalable representations that faithfully represent the content of the underlying data
  • Methods to synthesize information of different types and from different sources into a unified data representation
  • Methods and principles for representing data quality, reliability, and certainty measures throughout the data transformation and analysis process
Techniques and systems for production, presentation, and dissemination of analysis results
  • Methodology and tools that enable the capture of the analytic assessment, decision recommendations, and first responder actions into information packages
  • Technologies and systems that enable analysts to communicate what they know through the use of appropriate visual metaphor and accepted principles of reasoning and graphic representation
  • Techniques and tools that enable effective use of limited, mobile forms of technologies to support situation assessment by first responders
Methodologies and benchmarks for evaluating visual analytics techniques and systems
  • Infrastructure to facilitate evaluation of new visual analytics technologies
  • Ecologically valid evaluation methods for visual analytics tools

For fostering a stronger visual analytics community in the Asia-Pacific region, PacificVAST starts a new publishing model this year: ALL accepted papers will be published in a special issue of the Elsevier journal of Visual Informatics.

Important dates

TBA

Submission guidelines

TBA

WORKSHOP CHAIRS

PROGRAM COMMITTEE

TBA

Venue+Travel

VISA Information

We will handle the issuance of an invitation letter after you have finished doing advance registration. For us to help you, please send the following information at (the contact email address TBA):

Venue Information

PacificVis 2018 will be held on the Integrated Research Center of Kobe University, located in an artificial island called “Port Island” at City of Kobe, Hyogo Prefecture, Japan.

the Integrated Research Center of Kobe University (KUIRC)
the Integrated Research Center of Kobe University (KUIRC)

Integrated Research Center of Kobe University

The Integrated Research Center of Kobe University was founded in April 2011 for the purposes of promoting advanced interdisciplinary research, one of the University’s strengths, and exploring the social applications of research. Eight research projects in the newly-built research building (the west side of the main building) were launched in April 2011 and the hall building (the east side of the main building) was added in March 2012. In March 2015, the new annex building was completed with a total floor area of approximately 9,500 m2.

Address
7-1-48 Minatojimaminami-machi, Chuo-ku, Kobe 650-0047 Japan
Tel.
+81(0)78-599-6710
E-mail
ircpi-hall@office.kobe-u.ac.jp

About Kobe

Kobe is an international port city nestled below the beautiful Rokko mountain range and fronted by a tranquil blue inland sea, within the Seto Naikai National Park. People from 131 countries live here and provide Kobe with a colorful, vibrant and cosmopolitan character. As well as its sea port access, downtown Kobe is easily reached by air, road and rail. Kobe has its own domestic airport and the Kansai International Airport nearby. This is why Kobe has hosted more than 4,600 international conventions to date, and why it is one of Japanʼ s key convention cities. In 2013, the Japanese Government appointed Kobe as a ʻGlobal MICE Strategic Cityʼ on behalf of the nation.

More Info:

Travel Information

From Shikansen Shin-Kobe Station by subway
  1. Shinkansen Shin-Kobe Station – Kobe City Subway (about 2 min.) →
  2. Sannomiya Station – Port Liner bound for Kobe Airport (about 14min.) →
  3. K Computer Mae Station
From Kansai Airport
by Limousine bus
  1. Kansai Airport – Limousine bus (about 70 min.) →
  2. Sannomiya Station – Port Liner bound for Kobe Airport (about 14min.) →
  3. K Computer Mae Station
by Bay Shuttle (high-speed ferry)
  1. Kansai Airport — Bay Shuttle (about 30 min.) →
  2. Kobe Airport — Port Liner bound for Sannomiya (about 3 min.) →
  3. K Computer Mae Station
From Itami(Osaka) Airport using by Limousine bus
  1. Itami(Osaka) Airport — Limousine bus (about 40 min.) →
  2. Sannomiya Station — Port Liner bound for Kobe Airport (about 14min.) →
  3. K Computer Mae Station
From Kobe Airport
  1. Kobe Airport – Port Liner bound for Sannomiya (about 3 min.) →
  2. K Computer Mae Station
Access to KUIRC (pdf)
Access to KUIRC (pdf)

Organization

General Conference Chair


Takayuki Itoh
Ochanomizu University, Japan

Papers Co-Chairs


Stefan Bruckner
University of Bergen, Norway


Koji Koyamada
Kyoto University, Japan


Bongshin Lee
Microsoft Research, USA

PacificVAST Workshop Co-Chairs


Issei Fujishiro
Keio University, Japan


Jinwook Seo
Seoul National University, South Korea

Visualization Notes Co-Chairs


Kazuo Misue
University of Tsukuba, Japan


Filip Sadlo
University of Heidelberg, Germany


Lei Shi
Chinese Academic of Science, China

Posters Co-Chairs


Chongke Bi
Tianjin University, China


Masahiko Itoh
The University of Tokyo, Japan


Puripant Ruchikachorn
Chulalongkorn University, Thailand

Visual Storytelling Contest Chairs


Matthew Brehmer
Microsoft Research, USA


Ingrid Hotz
Linköping University, Sweden


Hidenori Watanave
Tokyo Metropolitan University, Japan

Steering Committee


Wei Chen
Zhejiang University, China


Issei Fujishiro
Keio University, Japan


Seokhee Hong
University of Sydney, Australia


Koji Koyamada
Kyoto University, Japan


Kwan-Liu Ma
University of California, Davis, USA


Jinwook Seo
Seoul National University, South Korea

Organizing Chair


Naohisa Sakamoto
Kobe University, Japan

Financial Chair


Yuriko Takeshima
Tokyo University of Technology, Japan

Local Arrangement Co-Chairs


Shigeo Takahashi
University of Aizu, Japan


Yosuke Onoue
Kyoto University, Japan


Jorji Nonaka
RIKEN AICS, Japan

Publication Chair


Hiroaki Natsukawa
Kyoto University, Japan

Publicity Chair


Ken Wakita
Tokyo Institute of Technology, Japan

Webmaster & Design Chair


Hsiang-Yun Wu
TU Wien, Austria

Program Committee

Visualization Notes Committee

Previous Events

Year City Date Link
2017 Seoul Apr 18 - Apr 21 Website
2016 Taipei Apr 19 - Apr 22 Website
2015 Hangzhou Apr 14 - Apr 17 Website
2014 Yokohama Mar 04 - Mar 07 Website
2013 Sydney Feb 26 - Mar 01 Website
2012 Songdo Feb 28 - Mar 02 Website
2011 Hong Kong Mar 01 - Mar 04 Website
2010 Taipei Mar 02 - Mar 05 Website
2009 Beijing Apr 20 - Apr 23 Website
2008 Kyoto Mar 04 - Mar 07 Website