Conference Information
BDSEA 2016: IEEE/ACM International Conference on Big Data Science, Engineering, and Applications
http://computing.derby.ac.uk/bdsea2016/
Submission Date:
2016-08-31 Extended
Notification Date:
2016-09-25
Conference Date:
2016-12-06
Location:
Shanghai, China
Years:
3
Viewed: 2802   Tracked: 7   Attend: 2

Conference Location
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Call For Papers
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.

Authors are invited to submit original unpublished manuscripts on a broad range of topics related to big data science, computing paradigms, platforms and applications.

Topics

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
Last updated by Dou Sun in 2016-08-17
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