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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 language | English |
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Title of host publication | Advanced Mathematical and Computational Tools in Metrology and Testing XII |
Editors | F Pavese, A B Forbes, N F Zhang, A G Chunovkina |
Place of Publication | Singapore |
Publisher | World Scientific Press |
Pages | 167-187 |
Number of pages | 21 |
ISBN (Electronic) | 978-981-124-239-7, 978-981-124-238-0 |
ISBN (Print) | 978-981-124-237-3 |
DOIs | |
Publication status | Published - 17 Feb 2022 |
Publication series
Name | Advances in Mathematics for Applied Sciences |
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Volume | 90 |
ISSN (Print) | 1793-0901 |
Keywords
- interval computations
- measurement uncertainty
- NP-hard problems
- monotonicity
- indirect measurements
- uncertainty quantification
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