The 5Vs of the data landscape: volume, variety, velocity, veracity, value

Big data science and foundations, analytics, visualization and semantics

Software and tools for big data management

Security, privacy and legal issues specific to big data

Big data economy, QoS and business models

Scientific discovery and business intelligence

Software, hardware and algorithm co-design, high-performance computing

Large-scale recommendation systems and graph analysis

Infrastructures and systems for big data analytics and managements

Middleware and tools for big data analytics and managements

Algorithmic, experimental, prototyping and implementation

Data quality issues: such as validation, metrics, optimizations and consistency

Data-driven innovation, computational modelling and data integration

Data intensive computing theorems and technologies

Big data for advanced manufacturing and productivity

Modelling, simulation and performance evaluation

Green data centers / environmental-friendly perspectives

Computing, scheduling and resource management for sustainability

Complex applications in areas where massive data is generated