DataCom 2017 - 2017 IEEE International Conference on Big Data Intelligence and Computing

Big data is a rapidly expanding research area spanning the fields of computer science and information management, and has become a ubiquitous term in understanding and solving complex problems in different disciplinary fields such as engineering, applied mathematics, medicine, computational biology, healthcare, social networks, finance, business, government, education, transportation and telecommunications.
The goal of the IEEE 2017 International Conference on Big Data Intelligence and Computing (IEEE DataCom 2017) is to establish an international forum for engineers and scientists to present their ideas and experiences in the fields of Big Data intelligence and computing. IEEE DataCom 2017 welcomes paper submissions on innovative work from researchers in academia, industry and government describing original research work in Big Data.
IEEE DataCom 2017 will be held on November 6-10, 2017, co-located with IEEE CyberSciTech 2017, IEEE DASC 2017 and IEEE PICom 2017, in Orlando, Florida
Scope and Topics
Topics of interest include, but are not limited to:
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