# BIM-Based Model Checking: A Scientometric Analysis and Critical Review
## 6 Conclusions  
The attention to BMC in the AEC field is increasing, and many new intelligent technologies are being introduced. In this study, a total of 145 research papers published between 2008 and 2024 were selected. In response to RQ1 set in Section 1, this study conducted scientometric analyses, including publication analysis, co-author analysis, keyword analysis, co-citation analysis, and cluster analysis, to visually demonstrate the research status and associations among articles. Furthermore, in response to RQ2, a critical review of BMC research was proposed based on the statistical data and analysis results, delving into significant topics. Finally, addressing RQ3 and RQ4, current challenges and future directions were summarized. These points have been proposed to provide recommendations for similar research and practice, with specific efforts and contributions as follows:  
1. Through the publication and co-authorship analysis, the overall situation of BMC has been presented. The research groups and regions that had made significant contributions were identified. The number of BMC publications peaked in 2016 and 2022. Although there were occasional decreases in certain years, overall, there was an increasing trend, indicating that BMC research has entered a mature phase. Among the authors, [PERSON], [PERSON], and [PERSON] were the most prolific first authors. The United States, China, and South Korea were the regions with the highest number of publications.
2. Through keyword co-occurrence networks and evolution networks, this study revealed the hot topics that researchers are focusing on and the changing trends in research interests. The most popular keywords were \"BIM\", \"ACC\", and \"NLP\". Over time, the keywords transitioned from \"design\" and \"compliance checking\" to the topics related to artificial intelligence, such as \"NLP\", \"deep learning\", and \"ARC\".
3. Through co-citation analysis and cluster analysis, this study revealed the associations among researchers, journals, and publications, reflecting their influence on other research. [PERSON], with the review article \"Automatic rule-based checking of building designs\" published in 2009, became one of the leaders in the BMC field. \"Automation in Construction\" and \"Advanced Engineering Informatics\" were identified as influential journals in this field. Based on the size ranking of title clusters, the prominent themes included \"Automatic rule-based checking\", \"Transformational rule\", and \"Semantic NLP-based information extraction\".
4. This study proposed three categories of challenges regarding rule classification, rule representation, and model quality evaluation. After gaining an in-depth understanding of the core content of all articles and combining it with quantitative data analysis, these challenges were summarized from the current research predicament. Amongthem, rule classification and representation are challenges that have not been thoroughly addressed, while model quality evaluation is a neglected, but crucial, aspect that therefore deserves more attention.
5. Based on the current significant trends in research and challenges faced, this study proposed four promising directions for future development, including unified policies and standards, the expansion of existing platforms, the interoperability of data, and NLP technology. Research in these directions has emerged but is not yet enough, warranting more effort to be invested.