Facilitating information exchange for 3D retrofit models of existing assets using Semantic Web technologies

Building Information Modelling (BIM) has gained a lot of momentum in new building projects in Architecture, Engineering, and Construction (AEC) for varying purposes like design, construction as well as Asset/Facilities Management (AM/FM). However, its use in existing buildings has been hampered by the challenges surrounding the limitations of available technologies used for generating retrofit models. In recent years, 3D laser scanning technology, as a remote sensing technique, has been extensively used to collect geometrical data from existing buildings. The output of this technology is a set of three-dimensional point measurements, also known as Point Cloud Data (PCD). In current practice, PCD is analysed and processed manually to generate BIM models utilising commercial BIM-driven platforms. Accordingly, several studies have been undertaken, proposing semi-automated approaches for generating parametric models by using PCD as the primary geometrical data source. An appropriate 3D model that is fit for purpose for a BIM-based process of design, construction, as well as operation and maintenance (O&M) of assets should incorporate geometrical and non-geometrical data. While the geometrical data can be extracted from the collected data, non-geometrical data may need to be appended to this for generating a genuinely semantically rich BIM model. On the other hand, a reliable data exchange framework could be beneficial within the AEC industry for O&M purposes. In this regard, a data exchange framework structured based on the Linked Data principles could be promising for creating a unified data format that would enhance the process of data exchange accordingly. This paper first outlines a framework proposed for generating semantically enriched 3D retrofit models for existing buildings by utilising the Resource Description Framework (RDF). RDF is utilised as a unified data format in the proposed framework to aggregate data captured from distributed offline and online data sources. The model, containing geometrical and non-geometrical data, is then generated through the conversion of RDF into IFC data model. However, the main focus of this paper is to propose a data exchange framework for populating the RDF data generated through the previously mentioned approach by using existing linked data schemas and vocabularies, such as Web Ontology Language for ifc (ifcOWL), Building Ontology Topology (BOT), Ontology for Managing Geometry (OMG),etc.