Applications and experiments in all areas of science are becoming increasingly complex and more demanding in terms of their computational and data requirements. Some applications generate data volumes reaching hundreds of terabytes and even petabytes. As scientific applications become more data intensive, the management of data resources and dataflow between the storage and compute resources is becoming the main bottleneck. Analyzing, visualizing, and disseminating these large data sets has become a major challenge and data intensive computing is now considered as the ''fourth paradigm'' in scientific discovery after theoretical, experimental, and computational science.

DataCloud 2012 will provide the scientific community a dedicated forum for discussing new research, development, and deployment efforts in running data-intensive computing workloads on Cloud Computing infrastructures. The DataCloud 2012 workshop will focus on the use of cloud-based technologies to meet the new data intensive scientific challenges that are not well served by the current supercomputers, grids or compute-intensive clouds. We believe the workshop will be an excellent place to help the community define the current state, determine future goals, and present architectures and services for future clouds supporting data intensive computing.
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WORKSHOP SCOPE

Topics of interest include, but are not limited to:

• Data-intensive cloud computing applications, characteristics, challenges
• Case studies of data intensive computing in the clouds
• Performance evaluation of data clouds, data grids, and data centers
• Energy-efficient data cloud design and management
• Data placement, scheduling, and interoperability in the clouds
• Accountability, QoS, and SLAs
• Data privacy and protection in a public cloud environment
• Distributed file systems for clouds
• Data streaming and parallelization
• New programming models for data-intensive cloud computing
• Scalability issues in clouds
• Social computing and massively social gaming
• 3D Internet and implications
• Future research challenges in data-intensive cloud computing

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ORGANIZERS

• Tevfik Kosar, University at Buffalo
• Ioan Raicu, Illinois Institute of Technology & Argonne National Laboratory, USA
• Roger Barga, Microsoft Research

STEERING COMMITTEE

• Ian Foster, University of Chicago & Argonne National Laboratory, USA
• Geoffrey Fox, Indiana University
• James Hamilton, Amazon Web Services
• Manish Parashar, Rutgers University & National Science Foundation
• Dan Reed, Microsoft Research
• Rich Wolski, University of California, Santa Barbara

PROGRAMME COMMITTEE

• Samer Al-Kiswany, University of British Columbia, Canada
• Abhishek Chandra, University of Minnesota
• Rong N. ChangI, BM Research
• Kyle Chard, University of Chicago & Argonne National Laboratory
• Terence Critchlow, Pacific Northwest National Laboratory
• Murat Demirbas, University at Buffalo
• Jaliya Ekanayake, Microsoft Research
• Geoffrey Fox, Indiana University
• Dennis Gannon, Microsoft Research
• Rob Gillen, Oak Ridge National Laboratory
• Maria Indrawan, Monash University, Australia
• Hui Jin, Oracle
• Dan Katz, National Science Foundation
• Steven Ko, University at Buffalo
• Reagan Moore, University of North Carolina
• Judy Qui, Indiana University
• Lavanya Ramakrishnan, Lawrence Berkeley National Laboratory
• Kui Ren, University at Buffalo
• Yogesh Simmhan, University of Southern California, USA
• Borjo Sotomayor, University of Chicago
• Wei Tang, Argonne National Laboratory
• Bernard Traversat, Oracle
• Zhifeng Yun, Louisiana State University
• Ziming Zheng, Illinois Institute of Technology