Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets
Open-source science builds on open and free resources that include data, metadata, software, and workflows. Informed decisions on whether and how to (re)use digital datasets are dependent on an understanding about the 'quality' of the underpinning data and relevant information. However, qu...
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Ubiquity Press
2022-03-01
|
| Series: | Data Science Journal |
| Subjects: | |
| Online Access: | https://datascience.codata.org/articles/1423 |
| _version_ | 1818188599202414592 |
|---|---|
| author | Ge Peng Carlo Lacagnina Robert R. Downs Anette Ganske Hampapuram K. Ramapriyan Ivana Ivánová Lesley Wyborn Dave Jones Lucy Bastin Chung-lin Shie David F. Moroni |
| author_facet | Ge Peng Carlo Lacagnina Robert R. Downs Anette Ganske Hampapuram K. Ramapriyan Ivana Ivánová Lesley Wyborn Dave Jones Lucy Bastin Chung-lin Shie David F. Moroni |
| author_sort | Ge Peng |
| collection | DOAJ |
| description | Open-source science builds on open and free resources that include data, metadata, software, and workflows. Informed decisions on whether and how to (re)use digital datasets are dependent on an understanding about the 'quality' of the underpinning data and relevant information. However, quality information, being difficult to curate and often context specific, is currently not readily available for sharing within and across disciplines. To help address this challenge and promote the creation and (re)use of freely and openly shared information about the quality of individual datasets, members of several groups around the world have undertaken an effort to develop international community guidelines with practical recommendations for the Earth science community, collaborating with international domain experts. The guidelines were inspired by the guiding principles of being findable, accessible, interoperable, and reusable (FAIR). Use of the FAIR dataset quality information guidelines is intended to help stakeholders, such as scientific data centers, digital data repositories, and producers, publishers, stewards and managers of data, to: i) capture, describe, and represent quality information of their datasets in a manner that is consistent with the FAIR Guiding Principles; ii) allow for the maximum discovery, trust, sharing, and reuse of their datasets; and iii) enable international access to and integration of dataset quality information. This article describes the processes that developed the guidelines that are aligned with the FAIR principles, presents a generic quality assessment workflow, describes the guidelines for preparing and disseminating dataset quality information, and outlines a path forward to improve their disciplinary diversity. |
| first_indexed | 2024-12-11T23:29:29Z |
| format | Article |
| id | doaj.art-c56a0087ddb9471791974a4b967068ca |
| institution | Directory Open Access Journal |
| issn | 1683-1470 |
| language | English |
| last_indexed | 2024-12-11T23:29:29Z |
| publishDate | 2022-03-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Data Science Journal |
| spelling | doaj.art-c56a0087ddb9471791974a4b967068ca2022-12-22T00:46:04ZengUbiquity PressData Science Journal1683-14702022-03-0121110.5334/dsj-2022-008856Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital DatasetsGe Peng0Carlo Lacagnina1Robert R. Downs2Anette Ganske3Hampapuram K. Ramapriyan4Ivana Ivánová5Lesley Wyborn6Dave Jones7Lucy Bastin8Chung-lin Shie9David F. Moroni10Earth System Science Center/NASA MSFC IMPACT, The University of Alabama in Huntsville, Huntsville, ALBarcelona Supercomputing Center (BSC), BarcelonaCenter for International Earth Science Information Network (CIESIN), Columbia University, Palisades, NYTIB – Leibniz Information Centre for Science and Technology, HannoverScience Systems and Applications, Inc., Lanham, MD; NASA Goddard Space Flight Center, Greenbelt, MDCurtin University, PerthNational Computational Infrastructure, Australian National University, ACTStormCenter Communications | GeoCollaborate, Halethorpe, MDAston University, BirminghamUniversity of Maryland at Baltimore County, Baltimore, MD; NASA Goddard Space Flight Center, Greenbelt, MDJet Propulsion Laboratory, California Institute of Technology, Pasadena, CAOpen-source science builds on open and free resources that include data, metadata, software, and workflows. Informed decisions on whether and how to (re)use digital datasets are dependent on an understanding about the 'quality' of the underpinning data and relevant information. However, quality information, being difficult to curate and often context specific, is currently not readily available for sharing within and across disciplines. To help address this challenge and promote the creation and (re)use of freely and openly shared information about the quality of individual datasets, members of several groups around the world have undertaken an effort to develop international community guidelines with practical recommendations for the Earth science community, collaborating with international domain experts. The guidelines were inspired by the guiding principles of being findable, accessible, interoperable, and reusable (FAIR). Use of the FAIR dataset quality information guidelines is intended to help stakeholders, such as scientific data centers, digital data repositories, and producers, publishers, stewards and managers of data, to: i) capture, describe, and represent quality information of their datasets in a manner that is consistent with the FAIR Guiding Principles; ii) allow for the maximum discovery, trust, sharing, and reuse of their datasets; and iii) enable international access to and integration of dataset quality information. This article describes the processes that developed the guidelines that are aligned with the FAIR principles, presents a generic quality assessment workflow, describes the guidelines for preparing and disseminating dataset quality information, and outlines a path forward to improve their disciplinary diversity.https://datascience.codata.org/articles/1423qualitytrustopen-source sciencefairguidelinesmetadata |
| spellingShingle | Ge Peng Carlo Lacagnina Robert R. Downs Anette Ganske Hampapuram K. Ramapriyan Ivana Ivánová Lesley Wyborn Dave Jones Lucy Bastin Chung-lin Shie David F. Moroni Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets Data Science Journal quality trust open-source science fair guidelines metadata |
| title | Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets |
| title_full | Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets |
| title_fullStr | Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets |
| title_full_unstemmed | Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets |
| title_short | Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets |
| title_sort | global community guidelines for documenting sharing and reusing quality information of individual digital datasets |
| topic | quality trust open-source science fair guidelines metadata |
| url | https://datascience.codata.org/articles/1423 |
| work_keys_str_mv | AT gepeng globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT carlolacagnina globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT robertrdowns globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT anetteganske globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT hampapuramkramapriyan globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT ivanaivanova globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT lesleywyborn globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT davejones globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT lucybastin globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT chunglinshie globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets AT davidfmoroni globalcommunityguidelinesfordocumentingsharingandreusingqualityinformationofindividualdigitaldatasets |