Computing in Science & Engineering
Extreme Data
Submissions due: March 2014
Estimated Publication date: November 2014
The current era of extreme data culled from a range of diverse data sources, ranging from extreme scale simulations to instruments, experiments, and pervasive sensors and systems, has the potential for revolutionizing science, engineering, and society in general. However, the expanding distribution and dynamism of the data, increasing data heterogeneity and uncertainty about its quality and availability, as well as the growing costs (time and energy) associated with transporting and processing this data, requires new paradigms and practices in data management and analytics, as well as supporting software stacks before this potential can be realized.
The goal of this special issue of CiSE is to explore the fundamental challenges ? as well as the state of the art in solutions ? of extreme data. From innovative algorithmic formulations to implementation frameworks and software stacks, what can accelerate insights from extreme data? End-to-end application workflows and relevant experiences with real applications are of particular interest.
Published by the IEEE Computer Society and the American Institute of Physics, CiSE magazine features the latest computational science and engineering research in an accessible format, along with departments covering news and analysis, CSE in education, and emerging technologies.
We strongly encourage submissions that include multimedia, data, and community content, which will be featured on the IEEE Computer Society website along with the accepted papers.
For more information please see http://www.computer.org/
Questions?
Contact guest editors Manish Parashar, Rutgers University (parashar at rutgers.edu) or George K. Thiruvathukal, Loyola University Chicago (gkt at cs.luc.edu).
Submission Guidelines
Authors are asked to submit high-quality original work that has neither appeared in nor is under consideration by other journals. All submissions will be peer-reviewed following standard journal practices. Manuscripts based on previously published conference papers must be extended substantially to include at least 30 percent new material. Manuscripts should be written in the active voice, should be no longer than 7,200 words (counting each standard figure and table as 250 words), and should follow the style and presentation guidelines of CiSE (see www.computer.org/cise/author for details).
Please submit your article using the online manuscript submission service at https://mc.manuscriptcentral.
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Ivan Rodero, Ph.D.
Rutgers Discovery Informatics Institute (RDI2)
NSF Center for Cloud and Autonomic Computing (CAC)
Department of Electrical and Computer Engineering
Rutgers, The State University of New Jersey
Office: CoRE Bldg, Rm 625
94 Brett Road, Piscataway, NJ 08854-8058
Phone: (848) 228-6474
Fax: (732) 445-0593
Email: irodero at rutgers dot edu
WWW: http://nsfcac.rutgers.edu/
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