[Call for Papers] BigData 2013 : 2013 IEEE International Conference on Big Data

Link: http://www.ischool.drexel.edu/bigdata/bigdata2013/callforpaper.htm

Oct 6, 2013 – Oct 10, 2013 (Silicon Valley, California, USA)
Submission Deadline: Jun 2, 2013
Notification Due: Aug 10, 2013
Final Version Due: Sep 1, 2013

Call for Papers

2013 IEEE International Conference on Big Data (IEEE BigData 2013)

October 6-9, 2013, Silicon Valley, CA, 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 International Conference on Big Data 2013 (IEEE BigData 2013) provides 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):: big data science and foundations, big data infrastructure, big data management, big data searching and mining, big data privacy/security, and big data applications. Relevant topics include but are not limited to:

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. Advanced database and Web Applications
b. Novel Data Model and Databases for Emerging Hardware
c. Data Preservation
d. Data Provenance‎
e. Interfaces to Database Systems and Analytics Software Systems
f. Data Protection, Integrity and Privacy Standards and Policies
g. Information Integration and Heterogeneous and Multi-structured Data Integration
h. Data management for Mobile and Pervasive Computing
i. Data Management in the Social Web
j. Crowdsourcing
k. Spatiotemporal and Stream Data Management
l. Scientific Data Management
m. Workflow Optimization
n. Database Management Challenges: Architecture, Storage, User Interfaces

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


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:

Prof. T.Y. Lin, San Jose State University, USA
Prof. Vijay Raghavan, Univ. of Louisiana at Lafayette, USA,
Prof. Benjamin Wah, Chinese Univ. of Hong Kong, China

Program Co-Chairs:

Dr. Ricardo Baeza-Yates, Yahoo! Labs, Spain
Prof. Geoffrey Fox, Indiana University, USA
Prof. Cyrus Shahabi, University of Southern California, USA
Prof. Matthew Smith, Leibniz Universität Hannove, Germany
Dr. Qiang Yang, Huawei Noah’s Ark Lab, China

Industry and Government Program Committee Chairs:

Mr. Rayid Ghani, Obama for America
Dr. Wei Han, Huawei Noah Ark Lab, China
Dr. Ronny Lempel, Yahoo! Labs, Israel
Dr. Raghunath Nambiar, Cisco Systems, USA

BIGDATA Steering Committee Chair:

Prof. Xiaohua Tony Hu, Drexel University, USA, thu@cis.drexel.edu

Paper Submission:

Please submit a full-length paper (upto 9 page IEEE 2-column format) through the online submission system:
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: June 2, 2013
Notification of paper acceptance: Aug 10, 2013
Camera-ready of accepted papers: Sept 1, 2013
Conference: October 6-9, 2013