[hpc-announce] CFP: The 3rd IEEE/ACM Conference on Big Data Science, Engineering and Applications (BDSEA), Shanghai, China

Ashiq Anjum Ashiq.Anjum at cern.ch
Thu May 26 11:08:06 CDT 2016

Call for Papers

The 3rd IEEE/ACM International Conference on Big Data Science, Engineering and Applications (BDSEA)

Date: December 6-9, 2016
Location: Shanghai, China
Website: http://computing.derby.ac.uk/bdsea2016/

Important Dates:
  - Paper Submission Due:  30 July, 2016
  - Author Notification:   21 August, 2016
  - Final Manuscript Due:  21 September, 2016

The IEEE/ACM International Conference on Big Data Science, Engineering, and Applications (BDSEA) is an annual international conference series. The first two events were held in London (BDC 2014) and Cyprus (BDC 2015) respectively. In 2016, the conference has been expanded to explicitly include application and renamed as BDSEA 2016. The conference series aims to provide a platform for researchers to present their new discoveries, developments, results, as well as the latest trends in big data computing and applications.

BDSEA 2016 will be held in conjunction with the 9th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2016) at Tongji University, Shanghai, China.

Topics of interest include, but are not limited to:

               I. Big Data Science
                              Big Data Analytics
                              Innovative Data Science Models and Approaches
                              Data Science Practice and Experience
                              Algorithms for Big Data
                              Novel Big Data Search Techniques
                              Innovative data and Knowledge Engineering approaches
                              Data Mining and Knowledge Discovery Approaches for Big Data
                              Big Data Acquisition, Integration, Cleaning, and Best Practices
                              Experience reports in Solving Large Scale Data Science Problems

               II. Big Data Infrastructures and Platforms
                              Scalable computing models, theories, and algorithms
                              In-Memory Systems and platforms for Big Data Analytics
                              Programming Systems for Big Data
                              Cyber-Infrastructures for Big Data
                              Performance evaluation reports for Big Data Systems
                              Fault tolerance and reliability of Big Data Systems
                              I/O and Data management Approaches for Big Data
                              Energy-efficient Algorithms
                              Storage Systems (including file systems, NoSQL, and RDBMS)
                              Resource management Approaches for Big Data Systems
                              Many-Task Computing
                              Many-core computing and accelerators

               III. Big Data Security and Policy
                              Big Data Archival and Preservation
                              Big Data Management Policies
                              Data Privacy
                              Data Security
                              Big Data Provenance
                              Ethical and Anonymization Issues for Big Data
                              Big Data Compliance and Governance Models

               IV. Big Data Applications
                              Experience Papers with Big Data Application Deployments
                              Big Data Applications for Internet of things
                              Scientific application cases studies on Cloud infrastructure
                              Big Data Applications at Scale
                              Data streaming applications
                              Mobile Applications of Big Data
                              Big Data in Social Networks
                              Healthcare Applications such as Genome processing and analytics
                              Enterprise Applications

               V. Visualization of Big Data
                              Visual Analytics Algorithms and Foundations
                              Graph and Context Models for Visualization
                              Analytical Reasoning and Sense-making on Big Data
                              Visual Representation and Interaction
                              Big Data Transformation, and Presentation

Programme Chair BDSEA 2016 -- http://computing.derby.ac.uk/bdsea2016/

Professor Ashiq Anjum, BE (Elect Eng), MSc (CS), PhD (CS), FHEA
Professor of Distributed Systems
Department of Computing and Mathematics
College of Engineering and Technology
University of Derby
Kedleston Road Derby, UK
DE22 1GB
Email: ashiq.anjum at cern.ch<mailto:ashiq.anjum at cern.ch> & a.anjum at derby.ac.uk<mailto:a.anjum at derby.ac.uk>
Phone: +44 (0) 1332 591881 & 44 (0) 772 4017071
Web: http://www.derby.ac.uk/staff/ashiq-anjum/

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