CALL FOR PAPERS

Workshop on Big Data Research and Development in Knowledge Engineering
In conjunction with
The 29th International Conference on Software Engineering and Knowledge Engineering (SEKE2017)

Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. With the advances of information communication technologies, it is critical to improve the efficiency and accuracy of modern data processing techniques. The past decade has witnessed the tremendous technical advances in Sensor Networks, Internet/Web of Things, Cloud Computing, Mobile/Embedded Computing, Spatial/Temporal Data Processing, and Big Data, and these technologies have provided new opportunities and solutions to data processing techniques. Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity).

This workshop wants to demonstrate the emerging issues in the research of Big Data and approaches towards the knowledge engineering. Original and research articles are solicited in all aspects including theoretical studies, practical applications, and experimental prototypes.

All submitted papers will be peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue. Potential topics include, but are not limited to:

Big data novel theory, algorithm and applications
Big data standards
Big data mining and analytics
Big data Infrastructure, MapReduce and Cloud Computing
Big data visualization
Big data semantics, scientific discovery and intelligence
Big data performance analysis and large-scale deployment
Knowledge Acquisition with big data
Knowledge-Based and Expert Systems with big data
Knowledge Representation and Retrieval with big data
Knowledge Engineering Tools and Techniques with big data
Time and Knowledge Management Tools with big data
Knowledge Visualization with big data

Submission:

Papers must be written in English. An electronic version (Postscript, pdf, or MS Word format) of the full paper should be submitted to the Big Data Research and Development Track using the following URL: https://www.easychair.org/conferences/?conf=seke2017 (submission website will be open after January 1, 2017). Please use Internet Explorer as the browser. Manuscript must include a 200-word abstract and no more than 6 pages of 2-column formatted Manuscript for Conference Proceedings (include figures and references but exclude copyright form).

Organizer:

Zheng Xu, Tsinghua University, China

Co-Organizers:

Yunhuai Liu, Hong Kong University of Science and Technology, Hong Kong
Neil Yen, Aizu University, Japan
Kim-Kwang Raymond Choo, University of South Australia, Australia
Vijayan Sugumaran, Oakland University, USA

Workshop Program Committee:

Shunxiang Zhang, Anhui Univ. of Sci. & Tech., China
Guangli Zhu, Anhui Univ. of Sci. & Tech., China
Tao Liao, Anhui Univ. of Sci. & Tech., China
Xiaobo Yin, Anhui Univ. of Sci. & Tech., China
Xiangfeng Luo, Shanghai Univ., China
Xiao Wei, Shainghai Univ., China
Kun Gao, Zhejiang Wanli Institute, China
Huan Du, Shanghai Univ., China
Zhiguo Yan, Fudan University, China