Special Issue on Big Data Research in China
Knowledge and Information Systems: An International Journal (KAIS)
(http://www.cs.uvm.edu/~kais/)
On March 5-7, 2013, the National Natural Science Foundation of China
(NSFC) organized the 89th Shuangqing Forum in Tongji University in
Shanghai on “Challenging Scientific Problems in Big Data Technologies
and Applications”. Big data refers to dynamic information that is
generated in complex systems and has the characteristics of huge quantity,
continuous sampling, multiple sources, and sparse values. Big data has
attracted tremendous attention from academia, industry, and the
government both within China and internationally. Big data research seeks
to extract useful information from massive data and use it to facilitate
our decision making. In the future, big data technologies are expected
to make full use of public data resources to realize digital and
intelligent transformations in areas such as traffic management,
logistics, health care, and education. However, the research on big data
technologies still has many challenges. Therefore, this Springer KAIS
special issue invites original research work on Big Data in China from
both the invited speakers from the above NSFC forum, and other established
researchers in this field. We aim to bring together innovative designs,
revolutionary ideas, and emerging applications of big data efforts.
Manuscripts are solicited to address all relevant topics in big data,
including but not limited to the following:
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Distributed high-speed access and high-performance computing
methods for dynamic big data
Theory and methods of high-speed transmission for dynamic big data
Theory and methods of compression sensing and machine learning for
dynamic big data
Dynamic big data analysis and processing methods
Theory and methods of modeling, optimization, and controlling
involving dynamic big data
Distributed fault diagnosis and maintenance theory and methods
involving dynamic big data
Theory and methods for distributed scheduling and multi-objective
decisions based on dynamic big data
Domain-oriented acquisition, maintenance, and demise of dynamic
big data
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Submission Guidelines
Submission information can be found on the journal home page
(http://www.cs.uvm.edu/~kais/) by clicking on "Submission Info" on the
sidebar. There are no specific page length restrictions. To submit your
article, follow the submission link, select "submit a manuscript", create
a user account, and, when prompted, choose "S.I.: Big Data" as the article
type. Please feel free to contact the guest editors with any questions.
Guest Editors
Jun ZHANG
Sun Yat-sen University, China
Email: issai@mail.sysu.edu.cn
Nanning ZHENG
Xi’an Jiaotong University
Email: nnzheng@mail.xjtu.edu.cn
Guest Editorial Board
Bin JIANG
Nanjing University of Aeronautics and Astronautics
Email: binjiang@nuaa.edu.cn
Hai JIN
Huazhong University of Science and Technology, China
Email: hjin@hust.edu.cn
Zhihua ZHOU
Nanjing University, China
Email: zhouzh@nju.edu.cn
Important Dates
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May 6, 2013: Submission Deadline
July 6, 2013: First-round Reviews
July 6, 2013: Revised Submissions
August 6, 2013: Acceptance Notifications
August 30, 2013: Final Manuscripts Due
Anticipated Publication: Early 2014
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