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