Website: http://www.swinflow.org/confs/2023/dikw/

Key dates:
Submission Deadline: August 25, 2023
Notification: October 15, 2023
Final Manuscript Due: October 30, 2023

Submission site: http://www.swinflow.org/confs/2023/dikw/submission.htm

Publication:
Proceedings will be published by IEEE CS Press. Distinguished papers will be invited to  special issues of selected journals listed on the conference website.

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Introduction
  
Data, Information, Knowledge and Wisdom, in short (DIKW), have been used widely as marking terms in various domains for expressing and exchanging semantic or conceptual subjective or objective understandings. However, there are still no unified understandings over the meaning of the DIKW concepts. Data, Information, Knowledge, and Wisdom as a whole concept of DIKW is also missing unified understandings of the relationships among them. Therefore, there have been proposals and models of DIKW as “layered hierarchy”, “architecture”, “framework”, “network”, “thinking mode”, “pattern”, “style”, “theory”, “methodology”, “model”, “graph”, etc.
  
2023 International Conference on Data, Information, Knowledge and Wisdom (DIKW 2023) aims to bring together scientists, researchers, and industrial engineers to exchange experimental and theoretical Data/Information/Knowledge/Wisdom modeling and processing results, novel designs, explainable AI, AI governance, work-in-progress and case studies on theories, design mechanisms and extensions on DIKW transformations and interactions in all areas, in all phases, empirical or theoretical solutions.
  
Scope and Topics
Topics of particular interest include, but are not limited to:
– Theories, Algorithms and Platforms for Data Analytics and Information Retrieving
– Data Provenance, Cleaning, Curation and Governance Services
– Data, Information, Knowledge and Wisdom Sharing, Integration and Migration
– Real-time Data Modeling and Information Provision Services and Applications
– Data-driven Intelligent Decision-making and Innovative Applications
– Goal or Purpose Models, Techniques and Tools for Smart Computing
– Data Models, Information Semantics, Query languages
– Data Stream Systems and Sensor Networks
– Data Visualization and Interactive Data Exploration
– Hybrid AI Privacy, Security, Trust, and Responsibility Provision
– Data-Knowledge Mixed Processing Systems and Service Architecture
– Domain Knowledge Modeling and Ontology-Building
– Data, Information and Knowledge Transformation Load balance
– DIKW content Storage and Retrieval and Interface Technology
– Software Tools for Data-Information-Knowledge Quality Modeling and Testing
– Computational Intelligence for Data, Information and Knowledge Hybrid Systems
– Multimedia and Cross-modals “Databases” Processing
– Development and Management of Heterogeneous Knowledge Bases
– Knowledge Extraction, Discovery, Analysis and Representation
– Application of Knowledge Representation Techniques to Semantic Modeling
– Optimization Techniques of DIKW applications
– Theories of DIKW Models and Performance Evaluation Approach  

Submission Guidelines
Submissions must include an abstract, keywords, the e-mail address of the corresponding author and should not exceed 8 pages for main conference, including tables and figures in IEEE CS format. The template files for LATEX or WORD can be downloaded here. All paper. submissions must represent original and unpublished work. Each submission will be peer reviewed by at least three program committee members. Submission of a paper should be regarded as an undertaking that, should the paper be accepted, at least one
of the authors will register for the conference and present the work. Submit your paper(s) in PDF file at the submission site: http://www.swinflow.org/confs/2023/dikw/submission.htm.

Publications
Proceedings will be published by IEEE CS Press. Distinguished papers will be invited to  special issues of selected journals listed on the conference website.  

General Chairs
Jianhua Ma, Hosei University, Japan    

Program Chairs
Muhammad Usman Khan, Federation University, Australia
Xiaolong Xu, Nanjing University of Information Science and Technology, China