# Ontology-Based Representation and Reasoning in Building Construction Cost Estimation in China
## 6 Conclusions  
The total lifecycle cost management of a project is of the greatest importance, and the automation of extraction and reasoning information for cost estimation is necessary and remains a challenge. In this research, we propose our research on the formalization and organization of cost estimation by means of ontology and this research is mainly focused on: hierarchy of building construction cost estimation concept; definition of OWL axiom and SWRL rules; and integration of heterogeneous information. This work is constructed in the context of the Chinese national mandatory specification GB 50500 and includes two aspects: (1) the ontology representation model including concept model ontology, work item ontology, and construction condition ontology; (2) the development of reasoning mechanism that automates the reasoning if a building construction cost estimation satisfies a set of these reasoning rules. Cost estimation examples are given to prove the feasibility and usability of the developed ontology model. The proposed method eliminates the need for manually updating a cost database. The related works of this research are summarized as follows:  
1. The hierarchical classification and reasoning rules are defined on the basis of GB 50500 and the terminology standard. This research solves the problem of localized standards by combining GB 50500 and the internationally accepted taxonomy standard. 2. The cost estimation ontology has the advantages of both consistency and clarity in its structure and concepts of expression. OWL can perfectly represent the knowledge of building construction cost estimation, and the ontology is convenient for sharing and reusing building construction cost estimation knowledge. 3. Reasoning rules can be described by SWRL in the building construction cost estimation ontology. Through the combination of SWRL and Jess inference engine, the reasoning results of cost estimation can be reasoned automatically. 4. This research demonstrates that the proposed ontologies and semantic reasoning rules can be utilized to facilitate cost estimation of concept and taxonomy structures in the proposed ontology. 5. Due to the powerful expansibility of the cost estimation ontology model, the cost information and rules in this proposed method can be continuously updated and expanded in practice, and automatic reasoning and integration of information can be realized. In addition, developing a mature building construction cost estimation ontology is a cumbersome task, and the theory and technology of the existing cost estimation model based on ontology are imperfect. Hence, a comprehensive comparison and analysis with the existing related ontologies and some related methods is outside the scope of this research. However, there are also some limitations of the proposed method that need to be studied in the future. First, there are still some limitations regarding ontology representation and reasoning in the proposed concept model ontology, work item ontology, and construction condition ontology. Due to the limitation of considering all possible construction conditions, which differ depending on the construction phase, the ontology model established in this research is simple; therefore, the  
Figure 16: Process of cost estimation. classes and their instances do not fully reflect the characteristics and their effects in actual cost estimation. Second, the study on building construction cost estimation ontology is still in its infant stage; thus, the number of classes and the relationships between classes are not sufficient to reflect the systematic and complex nature of cost estimation, and the cost estimation ontology needs to be improved continuously by collecting related information in the future. Finally, this research has not collected sufficient information to evaluate the proposed method, and there are not abundant data used for valid proof. The future research will adopt theoretical and empirical, qualitative and quantitative methods to evaluate the performance of the proposed method.