BIM and Linked Data Integration for Automated Compliance Checking: A Literature Review

Abstract

The construction industry is multidisciplinary. It requires strong collaboration andseamless data exchange between all engaged stakeholders across various projectphases, including design, construction, and operation. Within these phases, qualityand compliance control is essential. It ensures that the project meets requirementsand helps identify errors or missing information. However, traditional modelcontrol processes, which rely on manual methods conducted by people, are oftenerror-prone and time-consuming. To address these challenges, adoptingautomated workflows for compliance checking have become crucial to improveoverall efficiency and minimize errors in construction projects. Aligned with thisobjective, Building Information Modeling (BIM) has emerged as an effectivemethodology for data exchange and collaboration. Despite its advantages, theinformation contained in BIM models can be challenging to manage and is oftenoverlooked for updates, especially in large-scale projects. Integrating BIM withSemantic Web technologies significantly enhances its potential by enabling moreefficient automated compliance checking processes. The primary objective of thisresearch is to underline the potential of integrating Semantic Web technologieswith BIM methodologies for automated compliance checking. It aims to provide anoverview of the affordances, potentials, and limitations of these technologieswithin the Architecture, Engineering, Construction, Operations (AECO) domain,offering professionals a comprehensive technological foundation on how SemanticWeb technologies can be applied in combination with BIM methodologies. Withinthis scope, the paper particularly examines the use of Linked Data approaches ofthe Semantic Web, for automated compliance checking within the constructionindustry, by conducting a systematic literature review following the PreferredReporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.The findings highlight four key approaches, namely Web Ontology Language (OWL),Semantic Web Rule Language (SWRL), SPARQL Protocol and RDF Query Language(SPARQL), and Shapes Constraint Language (SHACL). Notably, SHACL emerges asthe most extensively adopted and suitable approach for automated ruleverification workflows within the broader Linked Data paradigm, as well as beingthe latest recommendation by the World Wide Web Committee (W3C). However,the existing literature also underscores persistent challenges, including thefrequent development of custom ontologies, limited reuse of validation rules, andthe absence of standardized constraint libraries. Overall, the research findingsdemonstrated that integrating Building Information Modeling with Linked Datatechnologies establishes a robust foundation for extendible and automatedcompliance verification, contributing to the rapid digital transformation within theAECO domain.