This study proposed a phased reverse engineering framework to construct cultural heritage archives using laser scanning and a building information model (BIM). This framework includes acquisition of point cloud data through laser scanning. Unlike previous studies, in this study, a standard for authoring BIM data was established through comparative analysis of existing archives and point cloud data, and a method of building valuable BIM data as an information model was proposed. From a short-term perspective, additional archives such as member lists and drawings can be extracted from BIM data built as an information model. In addition, from a long-term perspective, a scenario for using the cultural heritage archive consisting of historical records, point cloud data, and BIM data was presented. These scenarios were verified through a case study. In particular, through the BIM data building and management method, relatively very light BIM data (499 MB) could be built based on point cloud data (more than 917 MB), which is a large amount of data.

A variety of methodological approaches have been developed to performance assessment for the adoption of building information modeling (BIM) at organizational and project levels. Recently, active research has been undertaken on the quantitative analysis of the effects of BIM on projects through BIM-based design validation methodologies. Nevertheless, few studies have addressed the interactions between the BIM staff providing BIM services and the project participants requesting BIM services from the viewpoint of micro-level management. In this study, with the aim of improving the performance of BIM-based construction support, we performed an analysis of the properties of the BIM request for information (RFI) in the construction phase, proposing a method for performance analysis and assessment which considers the competencies of the BIM staff that handle and process such requests. This study verified that, through the application of a priority policy according to the purpose of the information use in the construction phase, the performance of the BIM staff can be improved, and the waiting time of project participants to receive responses to the BIM RFIs can be reduced. The findings of this study are expected to be applied in areas such as decision making on allocation of BIM staff and analysis of return on investment (ROI) in hiring BIM services.