Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud
The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/53669 |
| _version_ | 1848759199034507264 |
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| author | Mons, B. Neylon, Cameron Velterop, J. Dumontier, M. Da Silva Santos, L. Wilkinson, M. |
| author_facet | Mons, B. Neylon, Cameron Velterop, J. Dumontier, M. Da Silva Santos, L. Wilkinson, M. |
| author_sort | Mons, B. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in reality was largely open to interpretation. As support for the Principles has spread, so has the breadth of these interpretations. In observing this creeping spread of interpretation, several of the original authors felt it was now appropriate to revisit the Principles, to clarify both what FAIRness is, and is not. |
| first_indexed | 2025-11-14T09:56:05Z |
| format | Journal Article |
| id | curtin-20.500.11937-53669 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:56:05Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-536692017-10-06T06:00:07Z Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud Mons, B. Neylon, Cameron Velterop, J. Dumontier, M. Da Silva Santos, L. Wilkinson, M. The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in reality was largely open to interpretation. As support for the Principles has spread, so has the breadth of these interpretations. In observing this creeping spread of interpretation, several of the original authors felt it was now appropriate to revisit the Principles, to clarify both what FAIRness is, and is not. 2017 Journal Article http://hdl.handle.net/20.500.11937/53669 10.3233/ISU-170824 http://creativecommons.org/licenses/by-nc/4.0/ fulltext |
| spellingShingle | Mons, B. Neylon, Cameron Velterop, J. Dumontier, M. Da Silva Santos, L. Wilkinson, M. Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud |
| title | Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud |
| title_full | Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud |
| title_fullStr | Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud |
| title_full_unstemmed | Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud |
| title_short | Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud |
| title_sort | cloudy, increasingly fair; revisiting the fair data guiding principles for the european open science cloud |
| url | http://hdl.handle.net/20.500.11937/53669 |