BDAMS 2014 - International Workshop on Big Data Analytics, Management and Storage

Big data has shown great capability in yielding extremely useful information and extraordinary potential in revolutionizing scientific discoveries and traditional commercial models. Numerous corporations have begun to utilize big data to understand their customers’ behavior at a fine-grained level, rethink their business process workflow, and increase their productivity and competitiveness. Scientists are using big data to make new discoveries that were not possible before. As the volume, velocity, variety, and veracity of big data keep increasing, we are facing significant challenges with respect to innovative big data management, efficient big data analytics and low-cost big data storage solutions. This workshop aims to bring researchers and industry pioneers together to share their vision, discuss the ideas and demonstrate use cases on big data analytics, management and storage.
Topics of Interest
The topics of interest for this workshop include but are not limited to:
Novel Computational and Programming Models for Big Data
High Performance and Parallel Processing for Big Data
Big Data processing with Accelerators/Coprocessors (GPU, APU, MIC)
Effective Management of Commercial, Mobile and Social Big Data
Effective Management of Big Data in Scientific Computing
Workflow Optimization for Automated Big Data Analytics
Database Management Challenges: SQL and NoSQL
New Algorithms and Architectures for Big Data Analytics
Scalable and Low-cost Algorithms and Systems for Big Data Storage
Software and Hardware Architectures for Real-time Big Data Analytics
Energy efficiency of Big Data Analytics and Storage
Use Case of Big Data for Commercial Applications
Use Case of Big Data for Scientific Applications
Case Studies of Big Data Project Deployments
Industry Standards and Open Platforms for Big Data
Paper format, submission and selection
Authors are invited to submit original papers that must not have been submitted to or published in any other workshop, conference, or journal. The workshop will accept full papers describing completed work, work-in-progress papers with preliminary results, as well as short papers reporting inspiring and intriguing new ideas.
All papers should be submitted electronically (in PDF format) using the workshop submission system. The submission is limited to 6 pages and should follow the ASE BigData Science conference format requirements (paper styles).
All papers submitted to this workshop will be peer-reviewed and accepted based on their scientific merit and relevance to the workshop topics. Each submission should be regarded as an undertaking that, should the paper be accepted, at least one of the authors must attend the workshop to present the work in order for the paper to be included in the BigDataScience 2014 Workshops proceedings, which will be published by ACM and included in the ACM Digital Library (EI index).
Organizing committees
Program co-chairs:
Rong Ge, Marquette University
Ziliang Zong, Texas State University
Program committee:
Woongki Baek, Ulsan National Institute of Science and Technology
Michela Becchi, University of Missouri
Trishul M. Chilimbi, Microsoft Research
Song Fu, University of North Texas
Rong Ge, Marquette University
Rini Kaushik, IBM Research
Jian Li, IBM Research
Yu David Liu, SUNY Binghamton
Dong Li, Oakridge National Lab
Shaolei Ren, Florida International University
Suzanne Rivoire, Sonoma State University
Shuaiwen Song, Pacific Northwest National Lab
Ziliang Zong, Texas State University