There are various forms of database-assisted Building Information Modeling (BIM). For example, BIMQL is an open query language for building information models that leverages database integration. Other examples include IFC standards, specialized query systems for unique character pairs, and BIM software capable of conducting advanced searches. Additionally, topical analysis of 3D building models can be performed using spatial query languages that utilize databases to execute octree searches on these models. Let’s explore the relationship between BIM and databases.
Databases have the unique ability to store spatial information, which typically includes geometric properties such as points, lines, surfaces, volumes, and more complex data structures. Spatial queries generally fall into two categories: calculating spatial quantities and analyzing spatial geometry. Commonly used databases for these purposes include PostgreSQL and Geodedia, among others.
By combining the strengths of BIM and databases, along with a separation of concerns, BIM software can primarily focus on visualization and editing, while the database handles geometric calculations and complex queries. This division enables the creation of customized API programs to support more intricate or intertwined queries that require multiple functions working together.
Separating BIM and the database also allows for the development of a comprehensive set of SQL query methods. With a well-defined custom SQL syntax, queries can be combined or sorted flexibly to yield more precise results, granting users greater freedom and control over their data retrieval processes.
Using cloud storage to save files within the database enables remote users to work independently without interfering with one another. This approach facilitates collaborative workflows, similar to how Google Docs allows multiple users to edit cloud-based files simultaneously. Implementing this concept and designing the database architecture to support it are important areas for further research and development.
Today, smart sensing instruments come with a wide range of functions and styles. If building models are integrated within these sensors and their data stored in a database, it would greatly aid in analyzing various aspects of smart buildings in the future, such as green energy management, electricity consumption analysis, temperature monitoring, and more.
Transferring the geometric information from BIM into a database takes advantage of the database’s fast query capabilities. Calculations can be performed within the database and results sent back to the BIM component IDs for further use. Since geometric calculations are central to building information modeling, leveraging spatial data within the database can speed up program execution and position BIM as an effective information management hub during building operation and maintenance. Furthermore, during BIM application workflows, BIM models often serve as data control centers. Input data for many software programs originates from the properties of building components within the BIM model, while output data from one program may serve as input for another. This information flow is complex yet well-organized.
That concludes our overview of BIM and databases. I hope this information proves helpful to everyone.
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