Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets. (4th May 2021)
- Record Type:
- Journal Article
- Title:
- Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets. (4th May 2021)
- Main Title:
- Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets
- Authors:
- Peng, Ge
Downs, Robert R.
Lacagnina, Carlo
Ramapriyan, Hampapuram
Ivánová, Ivana
Moroni, David
Wei, Yaxing
Larnicol, Gilles
Wyborn, Lesley
Goldberg, Mitch
Schulz, Jörg
Bastrakova, Irina
Ganske, Anette
Bastin, Lucy
Khalsa, Siri Jodha S.
Wu, Mingfang
Shie, Chung-Lin
Ritchey, Nancy
Jones, Dave
Habermann, Ted
Lief, Christina
Maggio, Iolanda
Albani, Mirko
Stall, Shelley
Zhou, Lihang
Drévillon, Marie
Champion, Sarah
Hou, C. Sophie
Doblas-Reyes, Francisco
Lehnert, Kerstin
Robinson, Erin
Bugbee, Kaylin
… (more) - 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 qualityKnowledge 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. … (more)
- Is Part Of:
- Data science journal. Volume 20(2021)
- Journal:
- Data science journal
- Issue:
- Volume 20(2021)
- Issue Display:
- Volume 20, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 20
- Issue:
- 2021
- Issue Sort Value:
- 2021-0020-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-05-04
- Subjects:
- Data Quality -- Quality Dimension -- Earth Science Information -- Interoperability -- FAIR -- Stewardship
Science -- Data processing -- Periodicals
Database management -- Periodicals
502.85 - Journal URLs:
- http://datascience.codata.org/ ↗
http://www.codata.org/dsj/index.html ↗ - DOI:
- 10.5334/dsj-2021-019 ↗
- Languages:
- English
- ISSNs:
- 1683-1470
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 15833.xml