Knowledge-based automatic OpenBIM data exchanging framework supporting holistic building design

For complex building design, there are many factors required to be considered in order to achieve the best possible design. During the process, there are many different professionals using different tools, along with different information; it is therefore very difficult to enable efficient collaboration and decisions. Through a comprehensive literature review, the dissertation identifies that data exchange within the BIM context is still facing interoperability issues due to inconsistency in defining data exchange requirements. Moreover, the decision-making within the BIM context focuses on individual aspects, which are developed separately from each other and require end-users to have prior knowledge about other domains. Despite the effort to develop a multi-objective decision-making knowledge base, most research did not provide a method that can work in parallel with a BIM model, which can provide decisions based on the data collected from the BIM model automatically. Most methods require manual input to process the data in a BIM model. It hence requires a smart way to leverage diverse information sources to work together. Based on that, the dissertation determines the research motivation and formulates detailed research questions and hypotheses to establish an automatic data exchanging framework that combines both data exchange method and semantic web technology to eliminate inefficiencies in data exchange and improve the decision-making in the early design stage. A common data analysis (CDA) referencing various concepts such as the standardised Information Delivery Manual (IDM), model view definition (MVD) and the concept of the semantic intersection was designed to conclude single truth of information and partial truth of information data sets that form the basis for the proposed framework from a data processing perspective. Furthermore, the requirements needed for multi-objective knowledge were also investigated. Following the analysis, firstly, a data exchange method that can extract the critical data from a BIM model based on the IFC schema was implemented. Secondly, a multi-objective knowledge base is constructed, which can assist engineers who lack knowledge associated with sustainability and cost in comparing different design choices while considering design conditions to develop an ideal design in the early stage. The main outcome of the research lies in providing a multi-objective knowledge base that can closely connect with real-project data. Consequently, an automatic data acquisition method was developed to align the proposed knowledge base with the data exchange method to extract data from an IFC file and merge them with the data presented in the developed ontology automatically in order to eliminate the human involvement by decreasing manual input. It was shown that the proposed framework could provide different data sets and process the IFC-based BIM model correctly without data loss. The data acquisition method helped produce a more dynamic knowledge base that connects real project information to static information related to cost and sustainability efficiently. Consequently, this approach is proved to be more efficient than a manual approach by adding data to the knowledge base. The SWRL rules helped automate all the manual calculations and generate new facts based on the data in an IFC file. The built-in rules allow the end-user to review and compare different design alternatives by considering various factors at an early stage. All the developed tools and functions were tested and went through framework validation. This combined framework is unlike previous approaches where data and instances are entered manually one by one. It presents a more direct way to work with IFC-based BIM models in order to evaluate various aspects.