Modelling Metrological Traceability

Metrological traceability is essential for ensuring the accuracy of measurement results and enabling a comparison of results to support decision-making in society. This paper explores a structured approach to modelling traceability chains, focusing on the role of residual measurement errors and their impact on measurement accuracy. This work emphasises a scientific description of these errors as physical quantities. By adopting a simple modelling framework grounded in physical principles, the paper offers a formal way to account for the effects of errors through an entire traceability chain, from primary reference standards to end users. Real-world examples from microwave and optical metrology highlight the effectiveness of this rigorous modelling approach. Additionally, to further advance digital systems development in metrology, the paper advocates a formal semantic structure for modelling, based on principles of Model-Driven Architecture. This architectural approach will enhance the clarity of metrological practices and support ongoing efforts toward the digital transformation of international metrology infrastructure.

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Publication Details

Journal
Metrology
Published
2025-05-01
DOI
https://doi.org/10.3390/metrology5020025
Citations
1
Primary Topic
Scientific Measurement and Uncertainty Evaluation
Type
article
Field-Weighted Citation Impact
1.40
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article

Modelling Metrological Traceability

Blair D. Hall
1 citations
Metrology
Scientific Measurement and Uncertainty Evaluation
1.40
article

Modelling Metrological Traceability

Blair D. Hall
article en
1 citations

Abstract

Metrological traceability is essential for ensuring the accuracy of measurement results and enabling a comparison of results to support decision-making in society. This paper explores a structured approach to modelling traceability chains, focusing on the role of residual measurement errors and their impact on measurement accuracy. This work emphasises a scientific description of these errors as physical quantities. By adopting a simple modelling framework grounded in physical principles, the paper offers a formal way to account for the effects of errors through an entire traceability chain, from primary reference standards to end users. Real-world examples from microwave and optical metrology highlight the effectiveness of this rigorous modelling approach. Additionally, to further advance digital systems development in metrology, the paper advocates a formal semantic structure for modelling, based on principles of Model-Driven Architecture. This architectural approach will enhance the clarity of metrological practices and support ongoing efforts toward the digital transformation of international metrology infrastructure.

MetrologyVol. 5(2)
Statistics New Zealand (NZ), Measurement Standards Laboratory of New Zealand (NZ)
Openalex Percentile: Top 17%
Scientific Measurement and Uncertainty Evaluation
1.40
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