Important Dates

February 01, 2019

Workshop Proposal Due

April 14, 2019

Paper Submission Deadline

May 12, 2019

Authors Notification

June 02, 2019

Final Manuscript Due

July 14 - July 17, 2019

Conference Date



Photos of Cybermatics 2019

Note: Summit will be held in conference room Ansley 1 (14th floor).

July 16 keynote will be on GSU, then the remaining two days' breaks and parallel sessions as well as July 16 banquet and July 17 keynote will be resumed at Westin Hotel after 11am today. 8 rooms on the 14th floor and 2 rooms on the 12th floor, lunch and banquet will be on 6th floor, Chastain 2, and breaks will be on 14th floor.

Smart Data aims to filter out the noise 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 2019 IEEE International Conference on Smart Data (SmartData-2019) 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 of interest include, but are not limited to:

Track 1: Data Science and Its Foundations

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

Track 2: Big/Smart Data Infrastructure and Systems

  • Cloud/Cluster/Fog/Edge Computing for Big Data
  • Parallel Computing for Big Data
  • Open Source Big Data Systems (e.g., including Hadoop, Spark, Flink and Storm)
  • System Architecture and Infrastructure of Big/Smart Data
  • Big/Smart Data Appliance

Track 3: Big/Smart Data Storage and Management

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

Track 4: Big/Smart Data Processing and Analytics

  • Smart Data Search, Mining and Drilling from Big Data
  • Data Mining/Machine Learning/Deep Learning for Big/Smart Data
  • In-Memory/Streaming/Graph-Based Computing for Big/Smart Data
  • Brain/Nature-Inspired Computing for Big/Smart Data
  • Secure/Privacy-Preserving/Differentially Private Computing for Big/Smart Data
  • New Models, Algorithms, and Methods for Big/Smart Data Analytics
  • Visualization Analytics for Big Data

Track 5: Big/Smart Data Applications

  • Big/Smart Data Applications in All Fields,
e.g., Finance, Business, Healthcare, Transportation, Industry, Manufacture, Education, Telecommunication, etc.
  • Data as a Service (DaaS)
  • Security, Privacy and Trust in Big/Smart Data
  • Blockchain-Based Applications in Big/Smart Data
  • Big/Smart Data Opening, Sharing, Exchange and Trading
  • Practices and Experiences of Big/Smart Data Project Deployments
  • Ethic Issues in Big/Smart Data Applications

Conference History

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