The 2018 IEEE International Conference on Big Data (IEEE Big Data 2018) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications.

We solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. Example topics of interest includes but is not limited to the following:

Big Data Science and Foundations

• Novel Theoretical Models for Big Data
• New Computational Models for Big Data
• Data and Information Quality for Big Data
• New Data Standards

Big Data Infrastructure

• Cloud/Grid/Stream Computing for Big Data
• High Performance/Parallel Computing Platforms for Big Data
• Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
• Energy-efficient Computing for Big Data
• Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
• Software Techniques and Architectures in Cloud/Grid/Stream Computing
• Big Data Open Platforms
• New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
• Software Systems to Support Big Data Computing

Big Data Management

• Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
• Algorithms and Systems for Big Data Search
• Distributed, and Peer-to-peer Search
• Big Data Search Architectures, Scalability and Efficiency
• Data Acquisition, Integration, Cleaning, and Best Practices
• Visualization Analytics for Big Data
• Computational Modeling and Data Integration
• Large-scale Recommendation Systems and Social Media Systems
• Cloud/Grid/Stream Data Mining- Big Velocity Data
• Link and Graph Mining
• Semantic-based Data Mining and Data Pre-processing
• Mobility and Big Data
• Multimedia and Multi-structured Data- Big Variety Data

Big Data Search and Mining

• Social Web Search and Mining
• Web Search
• Algorithms and Systems for Big Data Search
• Distributed, and Peer-to-peer Search
• Big Data Search Architectures, Scalability and Efficiency
• Data Acquisition, Integration, Cleaning, and Best Practices
• Visualization Analytics for Big Data
• Computational Modeling and Data Integration
• Large-scale Recommendation Systems and Social Media Systems
• Cloud/Grid/StreamData Mining- Big Velocity Data
• Link and Graph Mining
• Semantic-based Data Mining and Data Pre-processing
• Mobility and Big Data
• Multimedia and Multi-structured Data-Big Variety Data

Big Data Security, Privacy and Trust

• Intrusion Detection for Gigabit Networks
• Anomaly and APT Detection in Very Large Scale Systems
• High Performance Cryptography
• Visualizing Large Scale Security Data
• Threat Detection using Big Data Analytics
• Privacy Threats of Big Data
• Privacy Preserving Big Data Collection/Analytics
• HCI Challenges for Big Data Security & Privacy
• User Studies for any of the above
• Sociological Aspects of Big Data Privacy
• Trust management in IoT and other Big Data Systems

Big Data Applications

• Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
• Big Data Analytics in Small Business Enterprises (SMEs)
• Big Data Analytics in Government, Public Sector and Society in General
• Real-life Case Studies of Value Creation through Big Data Analytics
• Big Data as a Service
• Big Data Industry Standards
• Experiences with Big Data Project Deployments