Supporting appraisal cost estimation by linked data

Abstract: The construction industry faces growing risks of execution defects and rising costs. A balance between quality and costs requires knowledge of quality-related costs. Despite increasing amounts of quality data, models predicting appraisal costs remain missing. This paper aims to determine expected appraisal costs from BIM objects using semantic web technologies and the ontology for construction quality assurance. The expected costs are determined automatically via SHACL rules and stored in the OCQA extension ontology for appraisal costs. To demonstrate the rules, the paper uses levelling methods and associated defect-type unevenness as examples.