One day between June 27-July 2 2013,
Santa Clara Marriott, CA, USA (Center of Silicon Valley)
within IEEE SERVICES 2013
Today, many science and engineering disciplines have become increasingly data-intensive. Massively complex new instruments and simulators are generating massive data sets that are described as big data. For example, in Physics, the Large Hadron Collider will eventually generate about 15 petabytes (1 petabye is about 1,000,000 gigabyes) of data per year. In neuroscience, a complete map of the brain's neural circuitry would generate about 1000 exabytes (an exabyte is about 1000 petabytes). The coming data deluge poses great challenges to the whole lifecycle of data management, from data collection, data storage, to data processing and visualization. In the meanwhile, workflow has become a popular paradigm for scientists and engineers to formalize and structure complex processes to solve increasingly data-intensive scientific and engineering problems. The importance of workflow is well recognized by NSF as well as by numerous workshops. As a recent Science article concluded, "In the future, the rapidity with which any given discipline advances is likely to depend on how well the community acquires the necessary expertise in database, workflow management, visualization, and cloud computing technologies."
The theme of this year's SWF workshop is "Advances in Workflows addressing the Big Data Challenge", recognizing the big data challenge in scientific workflows. Built upon the successful history of SWF (http://www.cs.wayne.edu/~shiyong/swf/) since 2007, this year, we broaden the scope of SWF to include big data oriented workflows, soliciting papers to share the challenges, experiences, and lessons in applying workflow technologies to various data-driven science and engineering problems. Topics of interests include, but are not limited to:
· Big-data workflows
· Data-driven workflows
· Event-driven workflows
· Scientific workflow provenance management and analytics
· Scientific workflow data, metadata, service, and task management
· Scientific workflow architectures, models, languages, systems, and algorithms
· Scientific workflow monitoring, debugging, exception handling, and fault tolerance
· Streaming data processing in scientific workflows
· Pipelined, data, workflow, and task parallelism in scientific workflows
· Cloud, Service, Grid, or hybrid scientific workflows
· Data, metadata, compute, user-interaction, or visualization-intensive scientific workflows
· Semantic techniques for scientific workflows
· Scientific workflow composition
· Security issues in scientific workflows
· Data integration and service integration in scientific workflows
· Scientific workflow mapping, optimization, and scheduling
· Scientific workflow modeling, simulation, analysis, and verification
· Scalability, reliability, extensibility, agility, and interoperability
· Scientific workflow applications and case studies
· Enterprise workflow management and services computing
· Enterprise workflow cooperation and collaboration
(Workshop chairs can grant extension to individuals under special circumstances provided that the hard deadline for the camera-ready version is respected.)
· Full Paper Submission Due Date: March 15, 2013
· Decision Notification (Electronic): April 4, 2013
· Camera-Ready Copy Due Date & Pre-registration Due: April 15, 2013
Authors are invited to submit full papers (about 8 pages) or short papers (about 4 pages) as per IEEE 8.5 x 11 manuscript guidelines (download instruction). All papers should be in PDF and submitted via at the submission system
First time users need to register with the system first. All the accepted papers by the workshops will be included in the Proceedings of the Seventh IEEE 2013 World Congress on Services (SERVICES 2013) which will be published by IEEE Computer Society.
· Liqiang Wang, firstname.lastname@example.org, University of Wyoming, U.S.A.
· Mike Wu, email@example.com, Oakland University, U.S.A.
· Ilkay Altintas, San Diego Supercomputer Center, USA
· Yong Zhao, University of Electronic Science and Technology of China, PR China
· Xiaoyu Ma (Veteran Affairs Hospital)
· Jamal Alhiyafi, University of Dammam, Saudi Arabia
· Ilkay Altintas, San Diego Supercomputer Center, U.S.A.
· Manish Anand, Salesforce, U.S.A.
· Adam Barker, University of St Andrews, U.K.
· Shawn Bowers, Gonzaga University, U.S.A.
· Bin Cao, Teradata Corporation, U.S.A.
· Artem Chebotko, University of Texas at Pan American, U.S.A.
· Jinjun Chen, Swinburne University of Technology, Australia
· Terence Critchlow, Pacific Northwest National Laboratory, U.S.A.
· Xubo Fei, Paypal Inc., U.S.A.
· Yi Gu, University of Tennessee at Martin, U.S.A.
· Thomas Hacker, Purdue University, U.S.A.
· Zoe Lacroix, Arizona State University, U.S.A.
· Cui Lin, California State University at Fresno, U.S.A.
· Wei Lu, Beijing Jiaotong University, China
· Murali Mani, University of Michigan at Flint, U.S.A.
· Marta Mattoso, Federal University of Rio de Janeiro, Brazil
· John Miller, University of Georgia, U.S.A.
· Paolo Missier, Newcastle University, U.K.
· Wei Tan, IBM T. J. Watson Research Center, U.S.A.
· Jianwu Wang, San Diego Super Computer Center, U.S.A.
· Qishi Wu, University of Memphis, U.S.A.
· Ping Yang, Binghamton University, U.S.A.
· Yong Zhao, University of Electronic Science and Technology of China, P.R. China
· Shiyong Lu, Wayne State University (Chair)
· Calton Pu, Georgia Tech