Duncan, P M; Smith, N A S; Romanchikova, M (2023) Metrology for data in life sciences, healthcare and pharmaceutical manufacturing: case studies from the National Physical Laboratory. Acta IMEKO, 12 (1). 10

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Abstract

In many disciplines, such as physics and engineering, the application of tools to support data metrology is encouraged and embedded in many processes and applications while in the life sciences, medicine and pharmaceutical manufacturing sectors these tools are often added as an afterthought, if considered at all. The use of data-driven decision making and the advent of machine learning in these industries has created an urgent demand for harmonised high-quality, instantly available, datasets across domains. The Findable, Accessible, Interoperable, Reproducible (FAIR) principles are designed to improve overall quality of research data. However, these principles alone do not guarantee that data is fit-for-purpose. Issues such as missing data and metadata, insufficient knowledge of measurement conditions or data provenance are well known and can be aided by applying metrological concepts to data preparation in order to increase confidence. This work presents the data metrology projects conducted by the National Physical Laboratory Data Science team in life sciences and healthcare domains

Item Type:	Article
Keywords:	NMI, metrology, digital pathology, medicines manufacturing, metadata standards, data quality, ontologies, FAIR principles
Subjects:	Mathematics and Scientific Computing > Modelling
Divisions:	Data Science
Identification number/DOI:	10.21014/actaimeko.v12i1.1406
Last Modified:	15 Jan 2024 14:26
URI:	http://eprintspublications.npl.co.uk/id/eprint/9898

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