[hpc-announce] CFP: Large Data Analysis and Visualization (LDAV) 2017

[Moreland, Kenneth]

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                              Call for Papers

              LDAV 2017 - Big Data Analysis and Visualization

   The 7th IEEE Symposium on Large Data Analysis and Visualization
                Held in conjunction with IEEE VIS 2017

                  October 2, 2017, Phoenix, Arizona, USA

                         http://www.ldav.org/

                       *** Abstracts due June 9 ***
                      *** Full Papers due June 16 ***

                       Contact: papers at ldav.org
                                     
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Modern large-scale scientific simulations, sensor networks, and experiments are
generating enormous datasets, with some projects approaching the multiple
exabyte range in the near term. Managing and analyzing large datasets in order
to transform it into insight is critical for a variety of disciplines including
climate science, nuclear physics, security, materials design, transportation,
and urban planning. The tools and approaches needed to mine, analyze, and
visualize data at extreme scales can be fully realized only if there are
end-to-end solutions, which demands collective, interdisciplinary efforts.

The 7th IEEE Large Scale Data Analysis and Visualization (LDAV) symposium, to
be held in conjunction with IEEE VIS 2017, is specifically targeting
methodological innovation, algorithmic foundations, and possible end-to-end
solutions. The LDAV symposium will bring together domain scientists, data
analysts, visualization researchers, and users to foster common ground for
solving both near- and long-term problems.

SCOPE:

We are looking for original research contributions on a broad-range of topics
related to collection, analysis, manipulation or visualization of large-scale
data. We also welcome position papers on these topics.

Topics of interest include, but are not limited to:

* Streaming methods for analysis, collection and visualization
* Advanced hardware for data handling or visualization
* Innovative software solutions and best practices for large data visualization
* Distributed, parallel or multi-threaded approaches
* Spark-based, MapReduce-based and database-related methods, algorithms 
  or approaches
* End-to-end system solutions in a large data context
* Hierarchical data storage, retrieval or rendering
* In situ visualization techniques
* Collaboration or co-design of large data analysis with domain scientists
* Topics in cognitive issues specific to manipulating and understanding 
  large data
* Application case studies
* Industry solutions for big data
* Innovative approaches combining information visualization, 
  visual analytics, and scientific visualization
* Novel methods for understanding and interacting with extreme-scale data
* New challenges in visualizing experimental, observational, or simulation data 
* Collection, management and curation of massive datasets

SUBMISSION INSTRUCTIONS:

Submitted manuscripts should have a length of 8 or 9 pages, with an
additional two (2) pages allowed only for references. Alternatively, authors
may submit short papers of 4-5 pages total length. The manuscripts should be
formatted according to guidelines from IEEE VGTC. Submission of an abstract is 
required prior to submission of a paper or short paper.

Submission site note: Go to the submission site
(https://precisionconference.com/~vgtc), log in, go to 'new submissions',
and select 'LDAV 2017 Papers'.

PROCEEDINGS:

The proceedings of the symposium will be published together with the
VIS proceedings and via the IEEE Xplore Digital Library.

BEST PAPER:

The LDAV Program Committee will present a Best Paper award to the
authors whose submission is deemed the strongest according to the
reviewing criteria. This award will be announced in conjunction with
VIS 2017.

IMPORTANT DATES:

Please note: all deadlines are firm and no extensions will be granted.

Abstract Deadline (firm):     June 9, 2017
Paper Submission (firm):      June 16, 2017, 11:59 PM (AOE)
Author Notification:          August 4, 2017
Camera-Ready Deadline (firm): August 11, 2017