Human-Centric Intelligent Systems - Call for Papers for the Special Issue: Responsible and Intelligent Knowledge Engineering

Guest Editors

Byeong Kang

Professor, School of ICT, University of Tasmania, Hobart, Australia

Qing Liu

Senior Research Scientist, Data61, CSIRO, Australia

Wenli Yang

Lecturer, School of ICT, University of Tasmania, Hobart, Australia

Aims and Scope

Intelligent knowledge engineering concerns the manipulation and transformation of data into knowledge. It is a multi-disciplinary research area including artificial intelligence/machine learning, knowledge acquisition and representation, knowledge reasoning, semantic web, data mining, high performance computing and many other fields. Each component of the knowledge engineering process, from heterogeneous data source and feature selection, to analysis algorithms and platforms, and how to represent the extracted knowledge to enhance human capability and experience with various applications, plays an important role to reach a conclusion and/or make a prediction. Despite the many benefits offered by intelligent knowledge engineering, its use raises many ethical concerns that cover the entire analytics processes. Responsible knowledge engineering challenges current practices to be built on solid ethical foundations.

Main topics and quality control

This special issue aims to bring recent progress on research, best practices, issues and challenges together that cover all aspects of intelligent knowledge engineering and responsible knowledge engineering. We invite original and unpublished RIKE-related contributions including but not limited to the following topics:

• Human-centric Knowledge Engineering

Human-machine collaboration, integration, interaction, delegation, dialog

• Responsible Data/Knowledge Engineering

Transparency, explainability, trust, accountability, fairness, privacy and security and other ethical concerns

• Knowledge Acquisition and Representation

Knowledge graph, knowledge representation learning and reasoning, temporal knowledge Graph

• Knowledge Discovering

Data mining, data linkage, machine learning/deep learning, semantic web

• Knowledge-aware Application

Question answering, recommendation system, domain-related application

• Other topics

Experience and lesson learned, reproducibility and negative results of knowledge Engineering

Full papers will be subject to a strict review procedure for final selection to this special issue based on the following criteria:

1. Quality and originality in theory and methodology of the special issue.

2. Relevance to the topic of the special issue.

3. Application orientation which exhibits novelty.

4. Free of potential bias.

5. Presence of the following statements (if applicable): disclosure of potential conflicts of interest, research involving human participants and/or animals, informed consent.

Important dates

Open date:                                   7 July 2022

Close date:                                   7 May 2023

Submit your paper

All papers have to be submitted via the Editorial Manager online submission and peer review system. Instructions will be provided on screen and you will be stepwise guided through the process of uploading all the relevant article details and files associated with your submission. During submission authors should indicate that their manuscript belongs to the special issue “Responsible and Intelligent Knowledge Engineering (RIKE)” (this question will appear at “Additional Information” step). All manuscripts must be in the English language.

To access the online submission site for the journal, please visit https://www.editorialmanager.com/hcin/ (this opens in a new tab) . Note that if this is the first time that you submit to the Human-Centric Intelligent Systems, you need to register as a user of the system first.

NOTE : Before submitting your paper, please make sure to review the journal's Author Guidelines (this opens in a new tab) first.

After Acceptance

This special issue will be published as a virtual collection that will be accessible at SpringerLink.

Accepted papers will be published online within about 20 days after acceptance, fully citable by DOI (Digital Object Identifier), prior to publication in the issue.

Introduction of the Guest Editors

[Byeong Kang]

University of Tasmania

Prof. Byeong Kang received the Ph.D. degree from the University of New South Wales, Sydney, in 1996. He was a Visiting Researcher with the Advanced Research Laboratory, HITACHI, Japan. He is currently a Professor in University of Tasmania. He leads the Smart Services and Systems research Group of postdoctoral scientists, which has carried out fundamental and applied research in research areas, expert systems, SNS analysis, and smart industry areas. His research interests include basic knowledge acquisition methods, and applied research in Internet systems and medical expert systems. He has served as the Chair and a Steering Committee Member of many international organizations and during conferences.

[Qing Liu]

Data61, CSIRO

Dr. Qing Liu is a senior research scientist in Data61 Software and Computational Systems Program, CSIRO. She holds her Ph.D. in Computer Science from the University of New South Wales. Her research focus on developing effective and efficient solutions for managing, integrating and analysing big data. Her recent interests involve responsible AI, knowledge graph, provenance management, trust computation and machine learning. She is the editor of the book "Data Provenance and Data Management for eScience”, published by Springer-Verlag. She has published many peer-reviewed articles in high-profile journals and conferences including SIGMOD, VLDB, AAMAS, ICDE, TrustCom, ISWC etc. She has served as co-chairs/pc/reviewer for international conferences and journals.

[Wenli Yang]

University of Tasmania

Dr. Wenli Yang received two Ph.D. degrees in Huazhong University of Science and Technology, Wuhan, China and University of Tasmania, Australia in 2012 and 2022, respectively. During her first Ph.D. degree, she also worked at the University of California at Davis, Davis, as a Visiting Scholar. She got the Associate Professor in China in 2016. She is currently a lecturer in University of Tasmania. Her research interests include image processing, machine learning/deep learning, data analytics, Knowledge-Based expert systems, blockchain, etc.