TY - UNPB

T1 - Dispute Resolution in Peer Review with Abstract Argumentation and OWL DL

AU - Прокудин, Дмитрий Евгеньевич

AU - Лисанюк, Елена Николаевна

AU - Баймуратов, Ильдар Раисович

PY - 2025

Y1 - 2025

N2 - The peer review process for scientific publications faces significant challenges due to the increasing volume of submissions and inherent reviewer biases. While artificial intelligence offers the potential to facilitate the process, it also risks perpetuating biases present in training data. This research addresses these challenges by applying formal methods from argumentation theory to support transparent and unbiased dispute resolution in peer review. Specifically, we conceptualize scientific peer review as a single mixed argumentative dispute between manuscript authors and reviewers and formalize it using abstract argumentation frameworks. We analyze the resulting peer review argumentation frameworks from semantic, graph-theoretic, and computational perspectives, showing that they are well-founded and decidable in linear time. These frameworks are then implemented using OWL DL and resolved with reasoning engines. We validate our approach by annotating a corpus of scientific peer reviews with abstract argumentation frameworks and applying a proof of concept to resolve the annotated disputes. The results demonstrate that integrating our method could enhance the quality of published work by providing a more rigorous and systematic approach to accounting reviewer arguments.

AB - The peer review process for scientific publications faces significant challenges due to the increasing volume of submissions and inherent reviewer biases. While artificial intelligence offers the potential to facilitate the process, it also risks perpetuating biases present in training data. This research addresses these challenges by applying formal methods from argumentation theory to support transparent and unbiased dispute resolution in peer review. Specifically, we conceptualize scientific peer review as a single mixed argumentative dispute between manuscript authors and reviewers and formalize it using abstract argumentation frameworks. We analyze the resulting peer review argumentation frameworks from semantic, graph-theoretic, and computational perspectives, showing that they are well-founded and decidable in linear time. These frameworks are then implemented using OWL DL and resolved with reasoning engines. We validate our approach by annotating a corpus of scientific peer reviews with abstract argumentation frameworks and applying a proof of concept to resolve the annotated disputes. The results demonstrate that integrating our method could enhance the quality of published work by providing a more rigorous and systematic approach to accounting reviewer arguments.

U2 - 10.48550/arXiv.2507.14258

DO - 10.48550/arXiv.2507.14258

M3 - Preprint

T3 - CoRR

BT - Dispute Resolution in Peer Review with Abstract Argumentation and OWL DL

ER -