Arbeitsgruppe Verteilte Systeme und Künstliche Intelligenz

August 22 - 25, 2022, Espoo, Finland

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-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.

* Important Dates

• Workshop Proposal: February 1, 2022
• Submission Deadline: 15 March, 2022
• Notification Due: 10th June, 2022
• Final Version Due: 25th June, 2022
• Conference Dates: 22-25 August, 2022

* 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/Graph Network/Meta 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 Deployment
• Ethic Issues in Big/ Smart Data

* Journal Special Issues

IEEE SmartData-2022 will invite additional submissions (after significant extension) to the special issue in the following prestigious journals:

• IEEE Internet of Things Journal (IF: 9.471)

• ACM Distributed Ledger Technologies: Research and Practice (ACM DLT)

• Information Sciences (Elsevier) (IF: 6.795)

• IEEE Network Magazine (TBD) (IF: 10.693)

• Information Fusion (Elsevier) (TBD) (IF: 12.975)

* Paper Submission

Main conference papers are limited to 8 pages (regular paper), or 6 pages (short paper), and 2-4 pages for a poster paper following the IEEE proceedings format, and are to be submitted as PDF via the site: (Coming soon).

* Paper Publication

Accepted conference papers will be published by IEEE (IEEE-DL and EI indexed). At least one author of each accepted paper is required to register and present their work at the conference; otherwise the paper will not be included in the proceedings. Selected papers, after further extensions and revisions, will be recommended to special issues. More details at the conference website: http://www.ieee-cybermatics.org/2022/smartdata/.

* Organizing Committees

General Chairs

Anke Schmeink, RWTH Aachen University, Germany

Houbing Herbert Song, Embry-Riddle Aeronautical University, USA

Guido Dartmann, Trier University of Applied Sciences, Germany

Program Chairs

Yongxin Liu, Auburn University, USA

Lejla Begic Fazlic, Trier University of Applied Sciences, Germany

Yaliang Zhao, Henan University, China

Workshop Chairs

Linglin Xia, Nanchang University, China

Steering Chairs

Laurence T. Yang (Chair), St Francis Xavier University, Canada

Zhikui Chen, Dalian University of Technology, China

Carson K. Leung, University of Manitoba, Canada

Publicity Chairs

Junyu Lu, Sichuan University, China

Jian Wang, University of Tennessee, USA

Leilei Yan, Soochow University, China

Web Chair

Jiawei Wang, St. Francis Xavier University, Canada

Dr. Lejla Begic-Fazlic and Prof. Dr. Guido Dartmann are PC Members at CPS & IoT 2021

Prof. Dr. Guido Dartmann is a guest editor for this special issue the IEEE IoT Journal