A comprehensive review of semantic web technologies supported life cycle management for road infrastructures

Zhang, Rujie, Wang, Jianwei, Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133 and Mao, Xinhua 2025. A comprehensive review of semantic web technologies supported life cycle management for road infrastructures. Alexandria Engineering Journal 128 , pp. 796-815. 10.1016/j.aej.2025.07.037

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Abstract

Aiming at a comprehensive understanding of semantic web technologies in enhancing digital intelligence of road infrastructure, 141 papers were selected for scientometric analysis and critical review. Research trends were visualized through co-authorship, co-citation, and co-word analyses, while critical reviews identified themes and limitations. Publication trends revealed growth peaks in 2016 and 2021 and shift toward journal-dominated outputs signaling maturation from exploratory methodologies to robust theoretical frameworks and practical validations. Co-authorship analysis revealed growing engineering-computer science collaborations, while co-citation analysis stressed foundational ontology methodologies. Keyword analysis identified essential themes including building information modeling, digital twins, and deep learning. Data exchange and semantic integration, knowledge management, and reasoning and simple querying were identified pivotal roles of semantic web technologies in road infrastructure. Subsequently, a preliminary framework was proposed synthesizing core components and key processes. Five limitations were identified: lack of comprehensive guiding framework and ontology development protocols; limited information integration and synchronization; insufficient automation; and weak capacity of logical inference and decision support. This paper contributes to the current knowledge body by providing insights into how semantic web technologies support the management of road infrastructures throughout life cycle and addressing concerns and limitations faced therein to offer suggestions for future advancement.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Engineering
Publisher:	Elsevier
ISSN:	1110-0168
Date of First Compliant Deposit:	3 August 2025
Date of Acceptance:	27 July 2025
Last Modified:	04 Aug 2025 09:00
URI:	https://orca.cardiff.ac.uk/id/eprint/180206

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