Ontology development for measurement process and uncertainty of results

• Main Authors: Priyanka Bharti, QingPing Yang, Alistair Forbes, Marina Romanchikova, Jean-Laurent Hippolyte
• Format: Article
• Language: English
• Published: Elsevier 2021-12-01
• Series: Measurement: Sensors
• Online Access: http://www.sciencedirect.com/science/article/pii/S2665917421002889

In future manufacturing and metrology, there is increasing demand to organize relevant metadata and knowledge to present information in semantically meaningful, reusable, easily accessible, and interoperable form. Up-to-date information on measurement uncertainty is key to interpretation of measurement results and to assessment of the quality of the measurement process. Although various technologies from knowledge engineering have been proposed to fulfil this requirement, previous work has not fully addressed the uncertainty during the measurement process. This paper presents the method to develop an ontology of the measurement process and the uncertainty of results on the example of coordinate measurements. The resulting ontology model based on a set of competency questions, including key concepts and relationships between them, is presented and discussed. The consistency of the ontology model is verified by inferencing rules and answering competency questions in Protégé software. The presented ontology will find wide applications in metrology and Industry 4.0.