Data provenance, curation and quality in metrology

James Cheney, Adriane Chapman, Joy Davidson, Alistair Forbes

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

Data metrology -- the assessment of the quality of data -- particularly in scientific and industrial settings, has emerged as an important requirement for the UK National Physical Laboratory (NPL) and other national metrology institutes. Data provenance and data curation are key components for emerging understanding of data metrology. However, to date provenance research has had limited visibility to or uptake in metrology. In this work, we summarize a scoping study carried out with NPL staff and industrial participants to understand their current and future needs for provenance, curation and data quality. We then survey provenance technology and standards that are relevant to metrology. We analyse the gaps between requirements and the current state of the art.
Original languageEnglish
Title of host publicationAdvanced Mathematical and Computational Tools in Metrology and Testing XII
EditorsF Pavese, A B Forbes, N F Zhang, A G Chunovkina
Place of PublicationSingapore
PublisherWorld Scientific Press
Pages167-187
Number of pages21
ISBN (Electronic)978-981-124-239-7, 978-981-124-238-0
ISBN (Print)978-981-124-237-3
DOIs
Publication statusPublished - 17 Feb 2022

Publication series

NameAdvances in Mathematics for Applied Sciences
Volume90
ISSN (Print)1793-0901

Keywords

  • interval computations
  • measurement uncertainty
  • NP-hard problems
  • monotonicity
  • indirect measurements
  • uncertainty quantification

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