Data structures in calibrations of weights and mass standards
Year: 2024
Type: article
Abstract: The paper addresses the transition from traditional to digital calibration certificates (DCC) for weights and mass standards, focusing on the critical aspect of machine interpretability. The main objective is to develop a methodology that converts human-readable calibration information into a format that can be processed by machines. To achieve this, the paper presents a structured approach for encoding information into the DCC framework, supplemented by practical examples that illustrate the fitting of data into the proposed structure. The study underscores the necessity of constructing semantic networks and formulating application rules to ensure consistency and harmonisation across DCCs for various weight and mass measurement devices. The results indicate that accurate digital representation of calibration information is paramount for the effectiveness of DCCs. The paper concludes by emphasising the current need for more advanced semantic networks to facilitate the seamless integration and interpretation of DCCs.
Source: Measurement Sensors
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,800
OpenAlex ID: W4405769501