Graph-Based Semantic BIM: A Comprehensive Review

The integration of Building Information Modeling (BIM) with semantic web technologies is crucial for addressing data interoperability and quality assurance challenges in the AEC industry. This paper presents a comprehensive bibliometric analysis of 234 documents from the Scopus database (2006-2024) to map the intellectual landscape of BIM and semantic data modeling using graph-based RDF representations. The analysis reveals a significant growth in publications, identifying key authors, countries, and the Automation in Construction journal as a leading publication venue. A co-occurrence network analysis delineates distinct research clusters, while trend analysis highlights a recent shift towards Artificial Intelligence (AI), machine learning, and natural language processing. By providing a structured overview of the field and pinpointing critical knowledge gaps, this study offers a valuable roadmap for future research into more intelligent, data-driven construction workflows.