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IEEE SmartData 2021 : 2021 IEEE International Conference on Smart Data

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Link: http://nsclab.org/smartdata2021/index.html
 
When Dec 6, 2021 - Dec 8, 2021
Where Melbourne, Australia
Submission Deadline Sep 5, 2021
Notification Due Oct 1, 2021
Final Version Due Oct 15, 2021
Categories    smart data
 

Call For Papers

IEEE SmartData-2021 Call for Papers
The 7th IEEE International Conference on Smart Data (SmartData 2021)
December 06 - 08, 2021, Melbourne, Australia
http://nsclab.org/smartdata2021/

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 modelling and analytics are indispensable for discovering the underlying structures of retrieved data and further acquiring smart data.

IEEE SmartData-2021 will be held in December 2021, Melbourne, Australia. 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.

* Important Dates
Paper Submission: September 5, 2021, AoE (Firm deadline without extension)
Notification of Acceptance: October 1, 2021, AoE
Registration and Camera-ready Due: October 15, 2021, AoE
Conference Dates: December 06 - 08, 2021, Monday-Wednesday

* Topics
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, and Drilling
  • Machine Learning/Deep Learning
  • In-Memory/Streaming/Graph-Based Computing
  • Brain/Nature-Inspired Computing
  • Secure/Privacy-Preserving/Differentially Private Computing
  • 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 Deployment
  • Ethic Issues in Big/ Smart Data

* Journal Special Issues
Selected papers presented at the IEEE Cybermatics Congress 2021 will be invited to consider submission (after significant extension) to the special issue in the following SCI-indexed journals:
  • IEEE Network Magazine
  • IEEE Internet of Things Journal
  • Telecommunication Systems
  • Journal of Ambient Intelligence and Humanized Computing
  • International Journal of Intelligent Systems
  • Mobile Information Systems
  • Cluster Computing
  • Journal of Signal Processing Systems
  • MDPI Electronics
  • MDPI Sensors

* Organizing Committees
General Chairs
Jiuyong Li, University of South Australia, Australia
Aniello Castiglione, University of Naples Parthenope, Italy

Program Chairs
Kai Qin, Swinburne University of Technology, Australia
Rajiv Ranjan, Newcastle University, UK

Publicity Co-Chairs
Longxiang Gao, Deakin University, Australia
Li Li, Monash University, Australia

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