Smart data aims to filter out 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 an 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 structures of retrieved data and further acquiring smart data.

IEEE SmartData-2022 will be held in August 2022, Espoo, Finland. It aims to promote community-wide discussions about identifying intelligent 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 in all aspects of smart data.

Topics of interest include, but are not limited to:

Track 1: Data Science and Its 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
  • In-Memory/Streaming/Graph-Based Computing
  • Brain/Nature-Inspired Computing
  • Secure/Privacy-Preserving/Differentially Private Computing
  • Federated Learning/Swarm Learning
  • New Models, Algorithms and Methods for Smart/Big Data Analytics
  • Visualization Analytics for Smart/Big Data

Track 5: Smart/Big Data Applications

  • Smart/Big Data Applications in All Fields
  • Data as a Service (DaaS)
  • Security, Privacy and Trust Applications in Smart/BigData
  • Smart/Big Data Opening, Sharing, and Trading
  • Practices and Experiences of Smart/ Big Data Project Deployments
  • Ethic Issues in Big/ Smart Data

• SmartData 2021, Melbourne, Australia
• SmartData 2020, Rhodes Island, Greece
• SmartData 2019, Atlanta, USA
• SmartData 2018, Halifax, Canada
• SmartData 2017, Exeter, UK
• SmartData 2016, Chengdu, China
• SmartData 2015, New York, USA