Metrological Traceability

A special issue of Metrology (ISSN 2673-8244).

Deadline for manuscript submissions: 31 December 2025 | Viewed by 3167

Special Issue Editor

Measurement Standards Laboratory of New Zealand, Lower Hutt 5010, New Zealand
Interests: measurement models; measurement uncertainty; software for metrology; quality infrastructure

Special Issue Information

Dear Colleagues,

Metrologically traceable measurements are essential when important societal decisions are based on physical data. The rigor provided by traceable measurement is crucial for making robust, reliable, trustworthy decisions. But what exactly is traceable measurement, and how can it be represented in digital form? These questions now concern many people working towards the digital transformation of measurement infrastructures.

A recent workshop stimulated discussion on this important topic. Organized by the CIPM Forum on Metrology and Digitalization, in partnership with several technical committees of IMEKO, the workshop examined traceability in today’s measurement infrastructure, which is built on principles established in the late 20th century. The workshop also explored traceability for new and emerging measurement system technologies, including intrinsic standards, sensor networks, virtual measuring systems, and virtual data spaces.

This Special Issue offers a platform for further and more detailed exchanges of ideas on these topics. Submissions are invited that shed light on the challenges posed by traceable measurement and its representation in the broader context of the digital transformation of the international measurement system.

Dr. Blair Hall
Guest Editor

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Keywords

  • metrological traceability
  • measurement standard
  • measurement uncertainty
  • quality infrastructure
  • calibration
  • digitalization
  • digital transformation

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Published Papers (3 papers)

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Research

17 pages, 2718 KB  
Article
Metrology for Virtual Measuring Instruments Illustrated by Three Applications
by Sonja Schmelter, Ines Fortmeier and Daniel Heißelmann
Metrology 2025, 5(3), 54; https://doi.org/10.3390/metrology5030054 - 1 Sep 2025
Viewed by 338
Abstract
In the course of digitalization, the importance of modeling and simulating real-world processes in a computer is rapidly increasing. Simulations are now in everyday use in many areas. For example, simulations are used to gain a better understanding of the real experiment, to [...] Read more.
In the course of digitalization, the importance of modeling and simulating real-world processes in a computer is rapidly increasing. Simulations are now in everyday use in many areas. For example, simulations are used to gain a better understanding of the real experiment, to plan new experiments, or to analyze existing experiments. Simulations are now also increasingly being used as an essential component of a real measurement, usually as part of an inverse problem. To ensure confidence in the results of such virtual measurements, traceability and methods for evaluating uncertainty are needed. In this paper, the challenges and benefits inherent to virtual metrology techniques are shown using three examples from different metrological fields: the virtual coordinate measuring machine, the tilted-wave interferometer, and the virtual flow meter. Full article
(This article belongs to the Special Issue Metrological Traceability)
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17 pages, 868 KB  
Article
Provenance in the Context of Metrological Traceability
by Ryan M. White
Metrology 2025, 5(3), 52; https://doi.org/10.3390/metrology5030052 - 21 Aug 2025
Viewed by 466
Abstract
This paper proposes using provenance information to describe processes in metrology. The PROV data model is used as an example to showcase a conceptual analysis about how to improve quality, reliability, and overall interoperability within cross-domain applications that require communicating measurement data and [...] Read more.
This paper proposes using provenance information to describe processes in metrology. The PROV data model is used as an example to showcase a conceptual analysis about how to improve quality, reliability, and overall interoperability within cross-domain applications that require communicating measurement data and traceability information. The analysis considers various metrological processes and outputs that support traceability. The conceptual analysis will be used as a foundation for further contributions to the topic of improving the documentation of metrological traceability with provenance data models. Several use cases illustrate how provenance information can provide context for traceability claims, especially when the measurement result is the focal object of interest. The PROV family of specifications provides machine-actionable metadata and semantic interoperability when communicating measurement information in traceability chains. PROV supports various perspectives that arise in the context of metrological traceability. Full article
(This article belongs to the Special Issue Metrological Traceability)
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25 pages, 466 KB  
Article
Modelling Metrological Traceability
by Blair D. Hall
Metrology 2025, 5(2), 25; https://doi.org/10.3390/metrology5020025 - 1 May 2025
Viewed by 1302
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Metrological Traceability)
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