Title: Selection of qualified reviewers and avoiding conflicts of interest within the issue of compromised peer review in paper retractions using an ontology-based decision support system

Authors: Mymoona Dawood Abdulmalek Al-Hidabi; Yunli Lee; Zaharin Yusoff; Phoey Lee Teh; Wai Chong Chia; Chukwudi Uwasomba

Addresses: School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500 Selangor Darul Ehsan, Malaysia ' Research Centre For Human-Machine Collaboration (HUMAC), School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500 Selangor Darul Ehsan, Malaysia ' IRDI International Medical University, Kuala Lumpur, Malaysia ' Department of Cyber and Computing, Faculty of Art, Computing and Engineering, Wrexham University, Wrexham, Wales, UK ' Research Centre For Human-Machine Collaboration (HUMAC), School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500 Selangor Darul Ehsan, Malaysia ' School of Computing and Communications, Open University, Milton Keynes, Buckinghamshire, UK

Abstract: Paper retractions are rising due to the absence of reliable tools to detect and identify fraudulent articles before publication. This paper proposes an ontology-based decision support system to prevent compromised peer review by carefully selecting qualified reviewers and avoiding potential conflicts of interest. There are three main contributions: (i) formulating the criteria for the selection of qualified reviewers as well as for recognising potential conflicts of interest; (ii) designing the ontology-based decision support system; (iii) designing and performing the methodology for validation. A pilot test with 30 computer science experts is conducted to determine qualified reviewers and conflict criteria, including the design of ontologies structure. Subsequently, three selected computer science experts and journal editors are requested to evaluate a set of test data as the ground truth. Overall results show that the proposed solution achieves 91% accuracy in qualified reviewer selection and 94% accuracy in conflict-of-interest detection.

Keywords: compromised peer review; credibility criteria; decision support system; knowledge representation; ontology.

DOI: 10.1504/IJMSO.2023.140701

International Journal of Metadata, Semantics and Ontologies, 2023 Vol.16 No.4, pp.298 - 314

Received: 11 Jan 2023
Accepted: 08 Nov 2023
Published online: 30 Aug 2024 *

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