[DL] IEEE Big Data 2016 Call for Papers

[CFP Conference]

*              Call for Papers*



*2016 IEEE International Conference on Big Data  (IEEE Big Data 2016)*



http://cci.drexel.edu/bigdata/bigdata2016/



Dec 5-8, 2016,  Washington DC, USA



In recent years, “Big Data” has become a new ubiquitous term. Big Data is
transforming science, engineering, medicine, healthcare, finance, business,
and ultimately our society itself. The IEEE Big Data conference series
started in 2013 has established itself as the top tier research conference
in Big Data.

·         The first conference IEEE Big Data 2013 had more than 400
registered participants from 40 countries (
http://cci.drexel.edu/bigdata/bigdata2013/) and the regular paper
acceptance  rate is 17.0%.

·         The IEEE Big Data 2015 had more than 780 registered participants
from 49 countries ( http://cci.drexel.edu/bigdata/bigdata2015/), and
regular paper acceptance rate is 16.8%.



 The 2016 IEEE International Conference on Big Data (IEEE Big Data 2016)
will continue the success of the previous IEEE Big Data conferences. It
will provide a leading forum for disseminating the latest results in Big
Data Research, Development, and Applications.



We solicit high-quality original research papers (and significant
work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs
(Volume, Velocity, Variety, Value and Veracity), including the Big Data
challenges in scientific and engineering, social, sensor/IoT/IoE, and
multimedia (audio, video, image, etc.) big data systems and
applications. *Example
topics of interest includes but is not limited to the following*:



1.      Big Data Science and Foundations

a.       Novel Theoretical Models for Big Data

b.      New Computational Models for Big Data

c.       Data and Information Quality for Big Data

d.      New Data Standards



2.      Big Data Infrastructure

a.       Cloud/Grid/Stream Computing for Big Data

b.      High Performance/Parallel Computing  Platforms for Big Data

c.       Autonomic Computing and Cyber-infrastructure, System
Architectures, Design and Deployment

d.      Energy-efficient Computing for Big Data

e.       Programming Models and Environments for Cluster, Cloud, and Grid
Computing to Support Big Data

f.       Software Techniques and Architectures in Cloud/Grid/Stream
Computing

g.      Big Data Open Platforms

h.      New Programming Models for Big Data beyond Hadoop/MapReduce, STORM

i.        Software Systems to Support Big Data Computing



3.      Big Data Management

a.       Search and Mining of variety of data including scientific and
engineering, social, sensor/IoT/IoE, and multimedia data

b.      Algorithms and Systems for Big DataSearch

c.       Distributed, and Peer-to-peer Search

d.      Big Data Search  Architectures, Scalability and Efficiency

e.       Data Acquisition, Integration, Cleaning,  and Best Practices

f.       Visualization Analytics for Big Data

g.      Computational Modeling and Data Integration

h.      Large-scale Recommendation Systems and Social Media Systems

i.        Cloud/Grid/Stream Data Mining- Big Velocity Data

j.        Link and Graph Mining

k.      Semantic-based Data Mining and Data Pre-processing

l.        Mobility and Big Data

m.    Multimedia and Multi-structured Data- Big Variety Data





4.      Big Data Search and Mining

a.       Social Web Search and Mining

b.      Web Search

c.       Algorithms and Systems for Big Data Search

d.      Distributed, and Peer-to-peer Search

e.       Big Data Search  Architectures, Scalability and Efficiency

f.       Data Acquisition, Integration, Cleaning,  and Best Practices

g.      Visualization Analytics for Big Data

h.      Computational Modeling and Data Integration

i.        Large-scale Recommendation Systems and Social Media Systems

j.        Cloud/Grid/StreamData Mining- Big Velocity Data

k.      Link and Graph Mining

l.        Semantic-based Data Mining and Data Pre-processing

m.    Mobility and Big Data

n.      Multimedia and Multi-structured Data- Big Variety Data



5.      Big Data Security, Privacy and Trust

a.       Intrusion Detection for Gigabit Networks

b.      Anomaly and APT Detection in Very Large Scale Systems

c.       High Performance Cryptography

d.      Visualizing Large Scale Security Data

e.       Threat Detection using Big Data Analytics

f.       Privacy Threats of Big Data

g.      Privacy Preserving Big Data Collection/Analytics

h.      HCI Challenges for Big Data Security & Privacy

i.        User Studies for any of the above

j.        Sociological Aspects of Big Data Privacy

k.      Trust management in IoT and other Big Data Systems





6.      Big Data Applications

a.       Complex Big Data Applications  in Science, Engineering, Medicine,
Healthcare, Finance, Business, Law, Education, Transportation, Retailing,
Telecommunication

b.      Big Data Analytics in Small Business Enterprises (SMEs),

c.       Big Data Analytics in Government, Public Sector and Society in
General

d.      Real-life Case Studies of Value Creation through Big Data Analytics

e.       Big Data as a Service

f.       Big Data Industry Standards

g.   Experiences with Big Data Project Deployments



*INDUSTRIAL Track*

The Industrial Track solicits papers describing implementations of Big Data
solutions relevant to industrial settings. The focus of industry track is
on papers that address the practical, applied, or pragmatic or new research
challenge issues related to the use of Big Data in industry. We accept full
papers (up to 10 pages) and extended abstracts (2-4 pages).



*Student Travel Award*

IEEE Big Data 2016 will offer* student travel *to student authors
(including post-docs)



*Journal Publication *

A set of about 10 papers will be selected for a fast-track review and then
published at the IEEE Transactions on Big Data.



*Conference Co-Chairs:*

Dr. Sudarsan Rachuri, DoE, USA

Prof. Lyle Ungar, University of Pennsylvania, USA

Prof. Philip S. Yu, University of Illinois at Chicago, USA

*Program Co-Chairs:*

Prof. James Joshi, University of Pittsburgh, USA

Prof. George Karypis, University of Minnesota, USA

Prof. Ling Liu, Georgia Institute of Technology, USA



*Industry and Government Program Committee Chairs*

Dr. Ronay Ak     NIST, USA

Dr. Rama Govindaraju, Google,USA

Dr. Toyotaro Suzumura, IBM Research, USA

Dr. Yinglong Xia, Huawei Research America, USA



*BigData Steering Committee Chair:*

Prof. Xiaohua Tony Hu, Drexel University, USA, xh29 at drexel.edu



*Paper Submission:*

Please submit a full-length paper (up to *10 page IEEE 2-column format*)
through the online submission system.

https://wi-lab.com/cyberchair/2016/bigdata16/scripts/submit.php?subarea=BigD

Papers should be formatted to IEEE Computer Society Proceedings Manuscript
Formatting Guidelines (see link to "formatting instructions" below).

*Formatting Instructions*
8.5" x 11" (DOC
<ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.doc>,
PDF
<ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.pdf>)

*LaTex Formatting Macros*
<ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_Latex8.5x11x2.zip>

*Important Dates:*



Electronic submission of full papers: July 25, 2016

Notification of paper acceptance: Oct 9, 2016

Camera-ready of accepted papers: Nov 5, 2016

Conference: Dec 5-8, 2016

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