Abstract: Currently, the lack of standardized support for ontology quality assessment models in the field of data governance is a significant issue. Building a standardized ontology quality assessment model is of utmost importance in addressing this challenge. By studying the dimensions under ISO/ IEC 25012 data quality standards, the GQM (Goal-Question-Metric) methodology is used as a guide to define metrics under the dimensions and realize the mapping from metrics to dimensions. Finally, based on the DQV(Data Quality Vocabulary)data quality model proposed by W3C(World Wide Web Consortium), a scalable and robust ontology quality model is constructed. The proposed quality assessment model provides a complete, unified, and standardized terminology system to describe the various elements of ontology quality, and provides a standardized quality knowledge representation model for ontology quality assessment. Finally, taking the completeness dimension as an example,the corresponding quality assessment model is constructed, and the feasibility of the model is verified by using the downhole operation data set. It effectively solves the problem of the lack of standardization of ontology quality assessment model in data governance field, and provides a unified and standardized term system to describe each element of ontology quality in data governance field. 

Key words: ontology evaluation, quality dimensions, quality assessment model, data quality vocabulary (DQV), goal-question-metric(GQM)