Thomas, S; Brochu, F (2021) A framework for traceble storage and curation of measurement data. Measurement: Sensors, 18. 100201

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Abstract

We outline a generic framework for capturing metadata from complex scientific experiments and linking these to data at the point of measurement. To digitally record metadata that may not be recorded in a machine-actionable way, we develop a simple and customisable webform based on a controlled dictionary. We implement our workflow for the CRUK Rosetta Grand Challenge Project which first combines metadata from multiple sources, including external sample or laboratory management systems, into a standard Extensible Markup Language schema. It then links the combined metadata with measurement data, and uploads the annotated data to a searchable database enabling automatic curation. This framework provides a workflow for establishing a metrologically FAIR (findable, accessible, interoperable, and reusable) traceable database. This unbroken chain of traceable measurements will improve confidence, repeatability, reuse, and longevity of data. Our standardised metadata is used to generate automatic reports of experimental methods for efficient error-free preparation of manuscripts.

Item Type:	Article
Keywords:	Reproducibility; Data curation; Data traceability; Metadata; FAIR data
Subjects:	Mathematics and Scientific Computing > Software Support for Metrology
Divisions:	Data Science
Identification number/DOI:	10.1016/j.measen.2021.100201
Last Modified:	14 Sep 2023 14:20
URI:	https://eprintspublications.npl.co.uk/id/eprint/9813