Data, Information, Knowledge and Wisdom, in short (DIKW), have been used widely as natural language marking terms in various domains for the purposes of expressing 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 has been proposals and models of DIKW as “layered hierarchy”, “architecture”, “framework”, “network”, “thinking mode”, “style”, “pattern”, “style”, “theory”, “methodology”, “model”, “graph”, etc.

Current scientific researches and engineering practices, as long as they aim at solving complexity based on precision and correction of conceptual sharing, are advancing ahead relying more and more on the solidification of the conceptual foundation. For example, to approaching strong AI involving art and social science in the direction of explainable AI, using current machine learning practice will need firstly not labeling ambiguous conceptual objects but identifying and clarifying the semantics of the concepts, possibly as advocated by Ludwig Wittgenstein, in an objective manner if possible.

Recently AI practices have already been approaching multiple modals learning targets in terms of voice, picture, text, etc, rapidly, in various domains not limited to neuroscience, biology, medicine, industrial 4.0, digital twins, security and privacy protection, design, etc. These approaches cover crossing multiple modals labeling, understanding, searching, reasoning, modification and especially and most recently embedding technologies in the form of various DIKW integration Machine Learning extensions. A foreseeable AI landscape with explainable and interactive human interactions is becoming feasible based on DIKW premises.

From the cognitive perspective, we propose to use multiple-modals for DIKW concepts as that Data modal as entity records of observations or abstraction of individual information with specific purposes, Information modal as purpose oriented relationships among DIKW targets, Knowledge modal as information typed with hypothesis of completeness, and Wisdom modal as human value bundled information. Towards the unification landscape of science and social science pictured in “Consilience: The Unity of Knowledge” by Dr. Edward O. Wilson, as DIKW modals are increasingly recognized as an important approach to solving problems related to semantic understanding beyond various question and answering systems, we are feeling more than ever the need to start by investigating on the necessary of unification of DIKW concepts in the background of relationship defined everything of semantics (RDXS) towards solving essence oriented computation and reasoning activities.

There might also be the cases that there will be new mode of Strong AI explorations such as we will not need to reach explicit unified understandings of the core concepts such as DIKW in the form of objective semantics but partially in the form of subjective semantics, which will still need supports or justification from crossing multiple disciplines, not limited to epistemology, cognitive psychology, philosophy, biology, social biology, etc.

Under this background, 2021 International Conference on Data, Information, Knowledge and Wisdom (DIKW 2021), which is co-organized by Hainan Association for Science and Technology and the DIKW research group of Hainan University, aims to bring together scientists, researchers, and industrial engineers to discuss and exchange experimental and theoretical results, novel designs, work-in-progress and case studies on theories, design mechanisms and extensions on Data, Information, Knowledge and Wisdom interactions in all areas, in all phases, empirical or theoretical solutions. We hope you will join us for the great gathering of outstanding science, engineering, and technology, and look forwards to seeing you in the beautiful city Haikou!

DIKW 2021 will be hosted in Haikou. Haikou is the capital city of Hainan Province which locates in southernmost part of China with the land area of 2284.49 square kilometers and the sea area of 861.44 square kilometers. Haikou is a tropical island city and comprises Hainan Island(part), Haidian island and Xinbu island. Haikou has a comfortable climate and first-class ecological environment, thus it is a world-renowned resort that attracts many people to visit each year.

Scope and Topics:

Topics of interest include, but are not limited to:

• Application of Knowledge Representation Techniques to Semantic Modeling
• Big Data and Inter Edge-Cloud Computing
• Cooperation in Heterogeneous Systems
• Data Integration, Metadata Management, and Interoperability
• Data, Information and Knowledge Sharing
• Data Mining and Knowledge Discovery
• Data Models, Information Semantics, Query languages
• Data Provenance, Cleaning, Curation
• Data Stream Systems and Sensor Networks
• Data Visualization and Interactive Data Exploration
• Database Privacy, Security, Trust and Design
• Development and Management of Heterogeneous Knowledge Bases
• Digital Libraries
• Domain Modeling and Ontology-Building
• Data, Information and Knowledge Security
• Information Storage and Retrieval and Interface Technology
• Management of Data, Information and Knowledge Hybrid Systems
• Multimedia and Crossmodals “Databases”
• Optimization Techniques of DIKW applications
• Theories of DIKW Models and Performance Evaluation Approaches

The materials presented in the papers should not be published or under submission elsewhere. Each paper is limited to 8 pages (or 10 pages with over length charge) including figures and references using IEEE Computer Society Proceedings Manuscripts style. Papers are to be submitted as PDF via the site: https://edas.info/N28866

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Once accepted, the paper will be included into the IEEE conference proceedings published by IEEE Computer Society Press (indexed by EI). At least one of the authors of any accepted paper is requested to register the paper at the conference.