A Unified Database Solution to Process BIM and GIS Data

For many years, the objective of spatial databases created using Geographic Information System (GIS) technology was to provide information about large spaces and areas outside of buildings. Building Information Modeling (BIM) technology focused mainly on small spaces, indoor and outdoor, targeted at other users and slightly different applications, was developed simultaneously for several dozen years. The significant development of GIS technology and new tools for quick data acquisition (e.g., laser scanning) and growing user needs resulted in the geoinformation modeling of the space inside buildings as well. BIM, on the other hand, began to be used for increasingly larger spaces outside buildings. Technology developers, users, and scientists started to notice that works turned out to be repetitive and that combining two different technologies is necessary; however, it is not simple. The research presented in the article is another attempt at connecting the world of BIM and GIS. The proposed integrated database environment of BIM/GIS spatial data makes it possible to store GIS and BIM data, enabling the use of the same data by both types of systems simultaneously and in a consistent manner. This allows BIM systems to to obtain simultaneous access to BIM and GIS data, which may be needed in, for example, the process of analyzing a building and its immediate surroundings. At the same time, GIS can obtain up-to-date building data necessary for spatial analyses, building management, or route mapping in navigation applications. The concept proposed in this article assumes a pragmatic approach, which is based on sharing Industry Foundation Classes (IFC) and CityGML schemas from a single database for BIM and GIS applications in their practically original form using an additional integrated BIM-GIS schema, called BIGI-S. The research joins some other works in this field, complementing them and adding a new perspective. This paper describes the concept of this solution, including specific data structures, data conversion algorithms, and a prototype solution. The tests carried out by the authors prove the robustness of the adopted concept and its technical feasibility.