[Ieee_vis] IEEE CG&A Theme Issue on Big Data Visualization

[Huamin Qu]

(Apologies for resending this CFPs. It is just a reminder that the
submission deadline is fast approaching.)  


CALL FOR PAPERS


Big Data Visualization


IEEE Computer Graphics and Applications' July/August 2013 issue


Submissions due: 30 November 2012


 <http://www.computer.org/portal/web/computingnow/cgacfp4>
http://www.computer.org/portal/web/computingnow/cgacfp4

We've entered a data-driven era, in which data are continuously acquired for
a variety of purposes. The ability to make timely decisions based on
available data is crucial to business success, clinical treatments, cyber
and national security, and disaster management. Additionally, the data
generated from large-scale simulations, astronomical observatories,
high-throughput experiments, or high-resolution sensors will help lead to
new discoveries if scientists have adequate tools to extract knowledge from
them. However, most data have become simply too large and often have too
short a lifespan. Almost all fields of study and practice sooner or later
will confront this big data problem. Government agencies and large
corporations are launching research programs to address the challenges
presented by big data. Visualization has been shown to be an effective tool
not only for presenting essential information in vast amounts of data but
also for driving complex analyses. Big data analytics and discovery present
new research opportunities to the computer graphics and visualization
community.

This theme issue of IEEE Computer Graphics and Applications aims to
highlight the latest advancements in solving the big data problems via
visual means. We solicit submissions on new techniques, systems, or tools
for making sense of big data, and we're also interested in works
demonstrating the value of big data when proper visualization and analytic
methods/systems are employed. The topics of interest include (but are not
limited to) the following:

.        information visualization for big data;

.        parallel visualization algorithms;

.        scalable visual analytics techniques;

.        novel visual analytics processes for big data;

.        integrated data reduction and visualization methods;

.        visual-based feature extraction and tracking algorithms;

.        visual analytics based on geometric/topological modeling;

.        augmented visual analysis of big data;

.        in situ data processing and visualization; and

.        visualization and visual analytics for scientific supercomputing,
experimental sciences, cyber intelligence and national security, business
strategies and services, environmental monitoring and emergency management,
astronomical/airborne/surveillance imagery, healthcare, and transportation
study.

Questions?

Contact Guest Editors

Daniel Keim, University of Konstanz, Germany ( <mailto:keim at uni-konstanz.de>
keim at uni-konstanz.de)
Kwan-Liu Ma, University of California-Davis, U.S.A. (
<mailto:ma at cs.ucdavis.edu> ma at cs.ucdavis.edu)
Huamin Qu, Hong Kong University of Science and Technology, Hong Kong (
<mailto:huamin at cse.ust.hk> huamin at cse.ust.hk)

Submission Guidelines

Articles should be no more than 8,000 words, with each figure counting as
200 words. Cite only the 12 most relevant references, and consider providing
technical background in sidebars for nonexpert readers. Color images are
preferable and should be limited to 10. Visit CG&A style and length
guidelines at  <http://www.computer.org/../../../cga/author.htm>
www.computer.org/cga/author.htm.

Please submit your article using the online manuscript submission service at
<https://mc.manuscriptcentral.com/cs-ieee>
https://mc.manuscriptcentral.com/cs-ieee. When uploading your article,
select the appropriate special-issue title under the category "Manuscript
Type." Also include complete contact information for all authors. If you
have any questions about submitting your article, contact the peer review
coordinator at cga-ma at computer.org.

 

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