Using large language models for semantic interoperability: A systematic literature review
Bilal Abu-Salih, Salihah Alotaibi, Albandari Lafi Alanazi, Ruba Abukhurma, Bashar Awad Al-Shboul, Ansar Khouri, Mohammed Abdullatif H. Aljaafari · ICT Express · 2025
Semantic Interoperability (SI) enables cross-domain data integration by allowing diverse systems to share and process information effectively. While existing reviews focus on general AI-driven interoperability, this systematic literature review (SLR) is the first to exclusively analyze the integration of Large Language Models (LLMs) with SI. This SLR uniquely evaluates LLMs' role in schema alignment, knowledge integration, and security risks. It also introduces a novel taxonomy and identifies challenges like bias propagation and computational costs, providing a new research framework for adversarial robustness, ethical AI, and real-world SI optimization. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).