The 2024 IEEE International Conference on Big Data (IEEE BigData 2024) 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. The conference adopts single-blind review policy. We expect to have a very high quality and exciting technical program at Washington DC USA this year. Example topics of interest includes but is not limited to the following: 1. 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 2. 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 3. Big Data Management Data Acquisition, Integration, Cleaning, and Best Practices Computational Modeling and Data Integration Large-scale Recommendation Systems and Social Media Systems Cloud/Grid/Stream Data Mining- Big Velocity Data Mobility and Big Data Multimedia and Multi-structured Data- Big Variety Data Compliance and Governance for Big Data 4. 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 Link and Graph Mining Semantic-based Data Mining and Data Pre-processing Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data 5. Big Data Learning and Analytics Predictive analytics on Big Data Machine learning algorithms for Big Data Deep learning for Big Data Feature representation learning for Big Data Dimension redution for Big Data Physics informed Big Data learning Visualization Analytics for Big Data 6. Data Ecosystem Data ecosystem concepts, theory, structure, and process Ecosystem services and management Methods for data exchange, monetization, and pricing Trust, resilience, privacy, and security issues Privacy preserving Big Data collection/analytics Trust management in Big Data systems Ecosystem assessment, valuation, and sustainability Experimental studies of fairness, diversity, accountability, and transparency 7. Foundation Models for Big Data Big data management for pre-training Big data management for fine-tuning Big data management for prompt-tuning Prompt Engineering and its Management Foundation Model Operationalization for multiple users 8. 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