A Novel HDF-Based Data Compression and Integration Approach to Support BIM-GIS Practical Applications

Abstract

Constructing a fully mapped virtual world is the premise of establishing the digital twin system; thus, the integration of BIM (Building Information Modeling) and GIS (Geographic Information System) constitutes a fundamental part of the mature digital twin. Although quite a few theoretical unified data models of BIM and GIS integration have been presented in precedent research, the practical web-based applications and software support for real-world city information modeling are still difficult to achieve. One of the challenges is storage inefficiency. It thence leads to burdens in exchange and analysis, which hugely impede the realization of virtual-real fusion. To address that issue, in this research, we contribute to exploring an HDF- (Hierarchical Data Format-) based, innovative, and synthesized scheme with three significant technical processes. First, data reorganization trims the original data with efficient redundancy elimination and reordering for IFC-SPF (IFC STEP Physical File) and XML-encoded CityGML (City Geography Markup Language). Next, bidirectional transformation methods for BIM and GIS modeling data, images, and analytical data into HDF are proposed. They retain the entities and relationships in modeling data and can further improve the compactness and accessibility by ultimately 60%–80% which saves 497,612 KB from 565,152 KB in the test of ZhongChun transformation substation. Finally, data aggregation enhances the bond of the integrated model and heterogeneous data resources from the transformed HDF files. The case studies show that the approach proposed in this paper could reach high efficiency for practicability of the BIM + GIS integration model. This light-weight integration method can further improve the front-end service responsiveness in digital twin applications.