Special Issue: "Crossing “Data, Information, Knowledge, and Wisdom” Models—Challenges, Solutions, and Recommendations"
Special Issue Editors
Interests: information security; artificial intelligence; big data; software engineering
Interests: e-commerce architectures; interoperability; social computing; decision support systems; IoT
Special Issue Information
Currently, most AI techniques and systems are built on hypotheses and assumptions of learning data distribution probabilities, information completeness, or logical consistency of knowledge systems, separately. However, it is hard to guarantee that learning data distribution will be as “big” as Big Data. Static data distribution is even more difficult in terms of modeling dynamics of data sets. Information completeness relies on not only various objective presentations of information but also the subjective purpose side inside human minds. Experience, common sense, and knowledge need coordination to keep conforming to the value of wisdom.
Data, information, knowledge, and wisdom (DIKW) have been used widely as natural language marking terms in various domains for the purposes of expressing understanding. However, there is a lack of common understanding over the meaning of DIKW concepts whether taken separately or combined. Therefore, there have been proposals and models of DIKW such as “layered hierarchy”, “architecture”, “framework”, “network”, “thinking mode”, “style”, “pattern”, “theory”, “methodology”, “model”, “graph”, etc. The more hypotheses and assumptions on the current uses of data, information, knowledge, and wisdom resources emerge, the less they can be used effectively and efficiently. These hypotheses and assumptions also mean a higher cost to collect, accumulate, and process relative resources.
Toward a more general AI landscape, which maps to real situations where we only have small or insufficient data, partial information, and diversified knowledge under a vague value strategy, with enriched processing capability, we propose to integrate the power or value of data, information, knowledge, and wisdom resources to fit more general AI application scenarios with less cost as well as improve effectiveness and efficiency through conversions among data, information, knowledge, and wisdom. In daily reality, we might expect proper imprecision, partial correctness, acceptable uncertainty, of data, information, knowledge, and wisdom, instead of overprecision, complete correctness, and full certainty, at an unexpected cost. In model merging and transformation among DIKW elements and DIKW architecture (e.g., data graph, information graph, knowledge graph, and wisdom graph), we expect the optimization of value-driven solutions toward the integration of efficiency and effectiveness catering to cross-cutting human purposes.
To tap into the benefits and uses of DIKW, the design principles and foundations of DIKW are expected to be explored to ensure an explainable and interactive AI landscape of crossing models based on DIKW premises. Aiming at investigating experimental and theoretical results, novel designs, this Special Issue will report the latest advances and developments in theories, design mechanisms, and extensions on data, information, knowledge, and wisdom interactions in all areas and phases, with empirical or theoretical solutions. The Special Issue will cover issues such as the uncertainties of multimodal content semantic traceability, relevance, migration, interaction, and the evolution of multimodal contexts or environments. This investigation should lead to new solutions toward complex content identification, modeling, processing, and service optimization in the context of massive content interaction in multidimensional, multimodal, multiscale physical and digital space covering data collection, information analysis, knowledge reasoning, and wisdom strategies in the background of the AI trend.
Topics for discussion in this Special Issue include but are not limited to:
- Application of knowledge representation techniques to semantic modeling
- Data integration, metadata management, and interoperability
- Data, information, and knowledge transformation/conversion
- Data mining and knowledge discovery
- Data models, information semantics, and query languages
- Data provenance, cleaning, and curation
- Data visualization and interactive data exploration
- Development and management of heterogeneous knowledge bases
- Domain modeling and ontology building
- Information storage and retrieval and interface technology
- Management of data, information, and knowledge hybrid systems
- Multimedia and cross-modal “Databases”
- Optimization techniques of DIKW applications
- Theories of DIKW models and performance evaluation techniques
- Crossing model interoperability inside and between applications
- Guidelines and best practices for DIKW architecture
- Privacy, trust, and security of DIKW architecture
Dr. Yucong Duan
Dr. Ejub Kajan
Dr. Zakaria Maamar
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Interannual variation of sea surface salinity in the South China Sea Based on satellite remote sensing
Authors: LUAN Xinrong
Affiliation: Ocean University of China
Abstract: In this paper, SMAP L3 sea surface salinity data from April 2015 to April 2021 and Argo grid data from January 2015 to December 2020 are selected to analyze the interannual variation of sea surface salinity in the South China Sea and its vicinity (including Beibu Gulf and Hainan Island). This paper mainly uses MATLAB and its extended package to merge and flatten the data, and obtains the consistency between SMAP satellite data and Argo data. By using SMAP data analysis, it comes to the conclusion that the north and south of SSS in the South China sea change greatly, while the central change is not obvious, and the interannual change of SSS in the South China Sea presents an upward trend.