[AISWorld] IEEE Big Data 2014 Call for Paper

[Xiaoli Song]

Call for Papers

2014 IEEE International Conference on Big Data (IEEE BigData 2014)

http://cci.drexel.edu/bigdata/bigdata2014/index.htm
October 27-30, 2014, 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 society itself. The IEEE Big Data has established itself as the top tier research conference in Big Data. The first conference IEEE Big Data 2013 ( http://cci.drexel.edu/bigdata/bigdata2013/ ) was held in Santa Clara , CA from Oct 6-7, 2013, more than 300 full paper submissions were received, 45 full papers and 50 short papers were presented, and more than 400 participants from 40 countries attend the 4-day event.

The IEEE International Conference on Big Data 2014 (IEEE BigData 2014) continues the success of the IEEE BigData 2013. It will provide a leading forum for disseminating the latest research in Big Data Research, Development, and Applications. 

We solicit high-quality original research papers (including significant work-in-progress) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity) relevant to variety of data (scientific and engineering, social, sensor/IoT/IoE, and multimedia-audio, video, image, etc) that contribute to the Big Data challenges. This 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 Data Search
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/Stream Data 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
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


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).



Conference Co-Chairs:
Dr. Charu Aggarwal, IBM T.J Watson Research, USA
Prof. Nick Cercone, York University, Canada
Prof. Vasant Honavar, Penn State University, USA

Program Co-Chairs:
Prof. Jimmy Lin, University of Maryland, USA
Prof. Jian Pei, Simon Fraser University, Canada

Industry and Government Program Committee Chair
Mr. Wo Chang, National Institute of Standard and Technology, USA
Dr. Raghunath Nambiar, Cisco Systems Inc, USA

BigData Steering Committee Chair:
Prof. Xiaohua Tony Hu, Drexel University, USA, thu at cis.drexel.edu 

Paper Submission:
Please submit a full-length paper (upto 9 page IEEE 2-column format) through the online submission system. 
http://wi-lab.com/cyberchair/2014/bigdata14/cbc_index.php
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, PDF) 
LaTex Formatting Macros
Important Dates:

Electronic submission of full papers: July 6, 2014 
Notification of paper acceptance: Aug 24, 2014
Camera-ready of accepted papers: Sept 25, 2014
Conference: October 27-30, 2014

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