Data provenance, curation and quality in metrology

James Cheney; Adriane Chapman; Joy Davidson; Alistair Forbes

doi:10.1142/9789811242380_0009

Data provenance, curation and quality in metrology

James Cheney, Adriane Chapman, Joy Davidson, Alistair Forbes

Research output: Chapter in Book/Report/Conference proceeding › Chapter (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 language	English
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
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	https://doi.org/10.1142/9789811242380_0009
Publication status	Published - 17 Feb 2022

Publication series

Name	Advances in Mathematics for Applied Sciences
Volume	90
ISSN (Print)	1793-0901

Keywords / Materials (for Non-textual outputs)

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

Access to Document

10.1142/9789811242380_0009Licence: All Rights Reserved

Cite this

Cheney, J., Chapman, A., Davidson, J., & Forbes, A. (2022). Data provenance, curation and quality in metrology. In F. Pavese, A. B. Forbes, N. F. Zhang, & A. G. Chunovkina (Eds.), Advanced Mathematical and Computational Tools in Metrology and Testing XII (pp. 167-187). (Advances in Mathematics for Applied Sciences; Vol. 90). World Scientific. https://doi.org/10.1142/9789811242380_0009

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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. ",

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Cheney, J, Chapman, A, Davidson, J & Forbes, A 2022, Data provenance, curation and quality in metrology. in F Pavese, AB Forbes, NF Zhang & AG Chunovkina (eds), Advanced Mathematical and Computational Tools in Metrology and Testing XII. Advances in Mathematics for Applied Sciences, vol. 90, World Scientific, Singapore, pp. 167-187. https://doi.org/10.1142/9789811242380_0009

Data provenance, curation and quality in metrology. / Cheney, James; Chapman, Adriane; Davidson, Joy et al.
Advanced Mathematical and Computational Tools in Metrology and Testing XII. ed. / F Pavese; A B Forbes; N F Zhang; A G Chunovkina. Singapore: World Scientific, 2022. p. 167-187 (Advances in Mathematics for Applied Sciences; Vol. 90).

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

TY - CHAP

T1 - Data provenance, curation and quality in metrology

AU - Cheney, James

AU - Chapman, Adriane

AU - Davidson, Joy

AU - Forbes, Alistair

PY - 2022/2/17

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N2 - 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.

AB - 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.

KW - interval computations

KW - measurement uncertainty

KW - NP-hard problems

KW - monotonicity

KW - indirect measurements

KW - uncertainty quantification

UR - https://www.worldscientific.com/series/samas

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M3 - Chapter (peer-reviewed)

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EP - 187

BT - Advanced Mathematical and Computational Tools in Metrology and Testing XII

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A2 - Forbes, A B

A2 - Zhang, N F

A2 - Chunovkina, A G

PB - World Scientific

CY - Singapore

ER -

Data provenance, curation and quality in metrology

Abstract

Publication series

Keywords / Materials (for Non-textual outputs)

Access to Document

Other files and links

Embargoed Document

Fingerprint

Turing Fellowship

Cite this

Data provenance, curation and quality in metrology

Abstract

Publication series

Keywords / Materials (for Non-textual outputs)

Access to Document

Other files and links

Embargoed Document

Fingerprint

Projects

Turing Fellowship

Cite this