The 11th IEEE International Conference on Smart Data (SmartData 2025) will be held in Zhengzhou, Henan, China, October 30- November 02, 2025. Smart data aims to filter out the noise data and produce valuable data, which can be effectively used by enterprises and governments for planning, operation, monitoring, control, and intelligent decision making. Although unprecedentedly large amount of sensory data can be collected with the advancement of the Cyber-Physical-Social systems, the key is to explore how big data can become smart data and offer intelligence. Advanced big data modeling and analytics are indispensable for discovering the underlying structure from retrieved data and further acquiring smart data.

The IEEE SmartData 2025 is to promote community-wide discussion identifying the computational intelligence technologies and theories for harvesting smart data from big data. It will provide a high-profile, leading-edge forum for scientists, engineers and researchers to discuss and exchange novel ideas, results, experiences and work-in-process on all aspects of smart data. Topics for submissions include but are not limited to the following theory, technology, and applications.

IEEE SmartData 2025 Tracks and Topics

Track 1: Data Science and lts Foundations

Foundational Theories for Data Science
Data Classification and Taxonomy
Data Metrics and Metrology
Data inference for Smart/Big Data
Theoretical Models for Smart/Big Data

Track 2: Smart/Big Data Infrastructure and Systems

Cloud/Cluster/Fog/Edge Computing
Parallel Computing for Big Data
Open Source Big Data Systems
System Architecture and Infrastructure
Smart/Big Data Appliance

Track 3: Smart/Big Data Storage and Management

Data Collection, Transformation and Transmission
Data Integration, Cleaning and Storage
Data Query and indexing Technologies
Distributed File/Database Systems
NewSQL/NoSQL for Smart/Big Data

Track 4: Smart/Big Data Processing and Analytics

Smart/Big Data Search, Mining, Drilling
Machine Learning/Deep Learning
Brain/Nature-Inspired Computing
Secure/Privacy-Preserving/Differentially Private Computing
Visualization Analytics for Smart/Big Data

Track 5: Smart/Big Data Applications

Parallel Computing for Big Data
Smart/Big Data Applications in All Fields
Data as a Service (DaaS)
Smart/Big Data Opening, Sharing, and Trading
Ethic lssues in Big/Smart Data

Track 6: Smart/Big Data in Internet of Things (loT)

Network Design, Scheduling and Optimization
Age of Information for Data Collection and Analytics in loT
Learning-based Decision-making with Smart/Big Data in loT
Mobile Data Collection, Transmission and Analytics in loT
New Models, Algorithms and Methods for Smart City