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Authors are invited to submit original unpublished manuscripts on a broad range of topics related to big data science, computing paradigms, platforms and applications.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