Exchanging data between different software systems is a critical requirement in the architecture, engineering, and construction industry, where task specific data models and public data exchange standards have been applied for data representation and exchange. Matching two data models effectively and efficiently is a challenging task, especially when performed manually, due to the large size and the complexity of today’s data schemas. Some existing computer-aided approaches have attempted to automate matching of different schemas. These approaches work and reduce human effort under specific conditions; however, they do not always result in an accurate matching of two schemas. Achieving schema matching result comparable in accuracy to manual matching requires leveraging domain specific knowledge. Yet utilization of domain knowledge for schema matching rarely has been incorporated in prior studies. In this paper, we present a semiautomated approach that leverages domain knowledge to improve the schema matching process. Compared to a generic schema matching approach, the approach discussed in this paper is able to generate more accurate results due to the incorporation of domain specific constraints, which are represented and reasoned with to create a match between data models. A prototype was developed to validate this approach through a number of real world test cases, including the matching of two publicly-available data exchange standards.