Call to action for global access to and harmonization of quality information of individual earth science datasets

Ge Peng; Robert R. Downs; Carlo Lacagnina; Hampapuram Ramapriyan; Ivana Ivánová; David Moroni; Yaxing Wei; Gilles Larnicol; Lesley Wyborn; Mitch Goldberg; Jörg Schulz; Irina Bastrakova; Anette Ganske; Lucy Bastin; Siri Jodha S. Khalsa; Mingfang Wu; Chung Lin Shie; Nancy Ritchey; Dave Jones; Ted Habermann; Christina Lief; Iolanda Maggio; Mirko Albani; Shelley Stall; Lihang Zhou; Marie Drévillon; Sarah Champion; C. Sophie Hou; Francisco Doblas-Reyes; Kerstin Lehnert; Erin Robinson; Kaylin Bugbee

doi:10.5334/dsj-2021-019

Call to action for global access to and harmonization of quality information of individual earth science datasets

Ge Peng^*, Robert R. Downs, Carlo Lacagnina, Hampapuram Ramapriyan, Ivana Ivánová, David Moroni, Yaxing Wei, Gilles Larnicol, Lesley Wyborn, Mitch Goldberg, Jörg Schulz, Irina Bastrakova, Anette Ganske, Lucy Bastin, Siri Jodha S. Khalsa, Mingfang Wu, Chung Lin Shie, Nancy Ritchey, Dave Jones, Ted HabermannChristina Lief, Iolanda Maggio, Mirko Albani, Shelley Stall, Lihang Zhou, Marie Drévillon, Sarah Champion, C. Sophie Hou, Francisco Doblas-Reyes, Kerstin Lehnert, Erin Robinson, Kaylin Bugbee

^*Corresponding author for this work

College of Engineering and Physical Sciences

Research output: Contribution to journal › Article › peer-review

Abstract

Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision-and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science.

Original language	English
Article number	19
Number of pages	15
Journal	Data Science Journal
Volume	20
Issue number	1
DOIs	https://doi.org/10.5334/dsj-2021-019
Publication status	Published - 4 May 2021

Bibliographical note

© 2021 The Author(s). This is an
open-access article distributed
under the terms of the Creative
Commons Attribution 4.0
International License (CC-BY
4.0), which permits unrestricted
use, distribution, and
reproduction in any medium,
provided the original author
and source are credited. See
http://creativecommons.org/
licenses/by/4.0/

Funding Information:
The virtual pre-ESIP workshop held on July 13, 2020 was sponsored by ESIP and co-organized by the ESIP IQC and the BSC EQC team, in collaboration with the ARDC AU/NZ DQIG. An additional community engagement event was carried out by the AU/NZ DQIG prior to the pre-ESIP workshop. ESIP is primarily supported by the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA) and the United States Geological Survey (USGS).

Keywords

Data Quality
Earth Science Information
FAIR
Interoperability
Quality Dimension
Stewardship

Access to Document

10.5334/dsj-2021-019

Call to action
© 2021 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/ licenses/by/4.0/
Final published version, 1.36 MBLicence: CC BY 3.0

Cite this

Peng, G., Downs, R. R., Lacagnina, C., Ramapriyan, H., Ivánová, I., Moroni, D., Wei, Y., Larnicol, G., Wyborn, L., Goldberg, M., Schulz, J., Bastrakova, I., Ganske, A., Bastin, L., Khalsa, S. J. S., Wu, M., Shie, C. L., Ritchey, N., Jones, D., ... Bugbee, K. (2021). Call to action for global access to and harmonization of quality information of individual earth science datasets. Data Science Journal, 20(1), Article 19. https://doi.org/10.5334/dsj-2021-019

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abstract = "Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision-and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science.",

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author = "Ge Peng and Downs, {Robert R.} and Carlo Lacagnina and Hampapuram Ramapriyan and Ivana Iv{\'a}nov{\'a} and David Moroni and Yaxing Wei and Gilles Larnicol and Lesley Wyborn and Mitch Goldberg and J{\"o}rg Schulz and Irina Bastrakova and Anette Ganske and Lucy Bastin and Khalsa, {Siri Jodha S.} and Mingfang Wu and Shie, {Chung Lin} and Nancy Ritchey and Dave Jones and Ted Habermann and Christina Lief and Iolanda Maggio and Mirko Albani and Shelley Stall and Lihang Zhou and Marie Dr{\'e}villon and Sarah Champion and Hou, {C. Sophie} and Francisco Doblas-Reyes and Kerstin Lehnert and Erin Robinson and Kaylin Bugbee",

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Peng, G, Downs, RR, Lacagnina, C, Ramapriyan, H, Ivánová, I, Moroni, D, Wei, Y, Larnicol, G, Wyborn, L, Goldberg, M, Schulz, J, Bastrakova, I, Ganske, A, Bastin, L, Khalsa, SJS, Wu, M, Shie, CL, Ritchey, N, Jones, D, Habermann, T, Lief, C, Maggio, I, Albani, M, Stall, S, Zhou, L, Drévillon, M, Champion, S, Hou, CS, Doblas-Reyes, F, Lehnert, K, Robinson, E & Bugbee, K 2021, 'Call to action for global access to and harmonization of quality information of individual earth science datasets', Data Science Journal, vol. 20, no. 1, 19. https://doi.org/10.5334/dsj-2021-019

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AU - Peng, Ge

AU - Downs, Robert R.

AU - Lacagnina, Carlo

AU - Ramapriyan, Hampapuram

AU - Ivánová, Ivana

AU - Moroni, David

AU - Wei, Yaxing

AU - Larnicol, Gilles

AU - Wyborn, Lesley

AU - Goldberg, Mitch

AU - Schulz, Jörg

AU - Bastrakova, Irina

AU - Ganske, Anette

AU - Bastin, Lucy

AU - Khalsa, Siri Jodha S.

AU - Wu, Mingfang

AU - Shie, Chung Lin

AU - Ritchey, Nancy

AU - Jones, Dave

AU - Habermann, Ted

AU - Lief, Christina

AU - Maggio, Iolanda

AU - Albani, Mirko

AU - Stall, Shelley

AU - Zhou, Lihang

AU - Drévillon, Marie

AU - Champion, Sarah

AU - Hou, C. Sophie

AU - Doblas-Reyes, Francisco

AU - Lehnert, Kerstin

AU - Robinson, Erin

AU - Bugbee, Kaylin

N1 - © 2021 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/ licenses/by/4.0/ Funding Information: The virtual pre-ESIP workshop held on July 13, 2020 was sponsored by ESIP and co-organized by the ESIP IQC and the BSC EQC team, in collaboration with the ARDC AU/NZ DQIG. An additional community engagement event was carried out by the AU/NZ DQIG prior to the pre-ESIP workshop. ESIP is primarily supported by the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA) and the United States Geological Survey (USGS).

PY - 2021/5/4

Y1 - 2021/5/4

N2 - Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision-and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science.

AB - Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision-and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science.

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KW - FAIR

KW - Interoperability

KW - Quality Dimension

KW - Stewardship

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ER -

Call to action for global access to and harmonization of quality information of individual earth science datasets

Abstract

Bibliographical note

Keywords

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