BDSEA 2016 : 3rd IEEE/ACM International Conference on Big Data Science, Engineering and Applications

December 06 - 09, 2016

China.

Call For Papers

Rapid advances in digital sensors, networks, storage, and computation along with their availability at low cost is leading to the creation of huge collections of data — dubbed as Big Data. This data has the potential for enabling new insights that can change the way business, science, and governments deliver services to their consumers and can impact society as a whole. This has led to the emergence of the Big Data Computing paradigm focusing on sensing, collection, storage, management and analysis of data from variety of sources to enable new value and insights. 

To realize the full potential of Big Data, we need to address several challenges and develop suitable conceptual and technological solutions for dealing them. These include life-cycle management of data, large-scale storage, flexible processing infrastructure, data modelling, scalable machine learning and data analysis algorithms, techniques for sampling and making trade-off between data processing time and accuracy, and dealing with privacy and ethical issues involved in data sensing, storage, processing, and actions. 

The International Conference on Big Data Science, Engineering and Applications (BDSEA) 2016 — held in conjunction with the 9th IEEE/ACM International Conference on Utility and Cloud Computing (UCC), December 6-9, 2016,Tongji University, Shanghai China, aims at bringing together international researchers, developers, policy makers, and users and to provide an international forum to present leading research activities, technical solutions, and results on a broad range of topics related to Big Data Science, Computing paradigms, platforms and their applications. The conference features keynotes, technical presentations, and workshops. 

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

Important Dates

Paper submission: July 30, 2016

                       

Notification of acceptance: August 21, 2016

           

Final manuscripts due: September 21, 2016

User Name : RNarmatha
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