2018 IEEE Conference on Big Data and Analytics (ICBDA-2018)

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 DataSearch

• 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

Big Data Models and Algorithms

• Foundational Models for Big Data

• Algorithms and Programming Techniques for Big Data Processing

• Big Data Analytics and Metrics

• Big Data Architectures

• Cloud Computing Techniques for Big Data

Big Data as a Service

• Big Data Open Platforms

• Big Data Management

• Big Data Persistence and Preservation

Big Data Quality and Provenance Control

• Big Data Storage and Retrieval

• Big Data Security and Privacy

• Big Data System Security and Integrity

Big Data Information Security

• Privacy Preserving Big Data Analytics

• Usable Security and Privacy for Big Data

• Quality of Big Data Services

• Business Intelligence

Technologies and Platforms

• Emerging hardware and software for data analytics

• Infrastructure and Portals

• Authoring and Content Management Tools

• Data Analytics Models

• e-business and New Media

• Delivery and Ethical Issues in Data Analytics

• Future Trends and Issues Data Analytics

• Data Mining

Infrastructure, Architecture and Tools

• Applications in Data Mining

• Innovative Models in Data Mining

• Statistics and Algorithms

• Future Trends and Issues in Data Mining

• Machine Learning

• Data Visualization

Issues/opportunities in Big Data

• Architecture and Technologies

• Trends in Data Visualization

• Data Visualization Applications

• Manufacturing and Cyber-physical models

• Industrial Practice, ethics and governance

• Big Data Service Performance Evaluation

Big Data Service Reliability and Availability

• Real-Time Big Data Services

• Big Data Search, Mining, and Visualization

• Algorithms and Systems for Big Data Search

Distributed, and Peer-to-peer Search

• Machine learning based on Big Data

• Visualization Analytics for Big Data

• Big Data Applications

• Big Data for Enterprise, Government, and Society

Case Studies of Big Data Value Creation

• Big Data for Science and Engineering Research

• Enabling Resources for Big Data Research

• Big Data Sets

Big Data Application Benchmarks

• Survey of big data research papers and/or big data sets

• Special Track on Real-Time Big Data Analytics

• Techniques and Algorithms for Real-Time Big Data Analytics

Applications and Evaluation of Real-Time Big Data Systems

• Special Track on Big Data/Smart Cities

• Big Data for Improving Resilient Infrastructures

• Big Data Applications such as Healthcare and Transportation