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Findable, Accessible, Interoperable,
and Reusable (FAIR) data
Kate LeMay Senior Research Data Specialist
kate.lemay@ardc.edu.au
International Funders
Journals
BMJ 2015;350:h2373
http://journals.plos.org/plosone/s/data-availability
http://www.nejm.org/doi/full/10.1056/NEJMe1601087#t=article
http://www.icmje.org/news-and-editorials/data_sharing_june_2017.pdf
ICMJE Recommendations for the Conduct, Reporting, Editing, and Publication of
Scholarly work in Medical Journals
Australian Funders
Open access policies
Australian Code for the Responsible Conduct of Research
Data management statement
required for national competitive
grants
www.arc.gov.au/policies-strategies/strategy/research-
data-management
National Statement on Ethical Conduct
in Human Research
Human Research Ethics Application
(HREA)
Advantages for researchers
• Transparency and reproducibility
• Maximises value of investment
• Citations and impact
• Collaborations
• Secure ongoing storage
• Ethical obligation (clinical trials)
• Publications with data cited more often
Data sharing/publication isn’t all ”open data”
Five Safes risk management framework
Image CCBY
http://archive.stats.govt.nz/browse_for_stats/snapshots-of-
nz/integrated-data-infrastructure/keep-data-safe.aspx
F.A.I.R. data principles
• Drafted in a workshop in 2014
• Nature article* and support by FORCE11
• Received international recognition
• Technology agnostic
• Discipline independent
• Both the data and the metadata
• Human readable and machine readable
Image by Sanja Pundir CC-BY-SA
* Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management
and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).
“FAIR principles provide ‘steps along a path’ toward machine-
actionability; adopting, in whole or in part, the FAIR principles, leads
the resource along the continuum towards this optimal state.”
Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data
management and stewardship. Sci. Data 3:160018 doi:
10.1038/sdata.2016.18 (2016).
Findable
• Describe your data
• Give it a persistent globally unique
identifier
• Make it findable through discipline
specific search routes and generic ones
F1. (meta)data are assigned a globally
unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in
a searchable resource.
F4. metadata specify the data identifier.
Accessible
• Accessibility is a spectrum
• Deposit in repository
• If not open, provide information how the
researcher can get access to the data and
background information (e.g. codebooks,
methods, software, algorithms)
A1 (meta)data are retrievable by their
identifier using a standardized communications
protocol.
A1.1 the protocol is open, free, and universally
implementable.
A1.2 the protocol allows for an authentication
and authorization procedure, where necessary.
A2 metadata are accessible, even when the data
are no longer available.
Open Mediated Closed
Interoperable
• Use a standard file format
• Use a community agreed vocabulary
(MeSH, SNOMED CT, ICD-10…)
• Link to relevant information
I1. (meta)data use a formal, accessible,
shared, and broadly applicable
language for knowledge representation.
I2. (meta)data use vocabularies (and
ontologies) that follow FAIR principles.
I3. (meta)data include qualified
references to other (meta)data.
Reusable
Other aspects on top of F.A.I. :
• Discipline specific information about the
output
• Information on how the data was
created
• A machine readable licence
(Creative Commons recommended, see
our licensing guide
ands.org.au/guides/copyright-data-and-
licensing)
R1. meta(data) have a plurality of accurate
and relevant attributes.
R1.1. (meta)data are released with
a clear and accessible data usage license.
R1.2. (meta)data are associated with
their provenance.
R1.3. (meta)data meet domain-relevant
community standards.
F.A.I.R resources
Icons made by Freepik are licensed by CC BY 3.0
Entire FAIR resources graphic is licensed under a Creative Commons
Attribution 4.0 International License
ands.org.au/working-with-data/fairdata
Self assessment tool
Sensitive data resources
ands.org.au/working-with-data/sensitive-data
Publishing and
sharing sensitive data
Guide
Data sharing considerations for Human
Research Ethics Committees Guide
De-identification Guide
With the exception of third party images or where otherwise indicated, this work is licensed under the Creative Commons Attribution 4.0 International Licence.
The ARDC is supported by the Australian Government through the National Collaborative Research Infrastructure
Strategy Program
Kate LeMay Senior Research Data Specialist
kate.lemay@ardc.edu.au
@katelemayardc

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Findable, Accessible, Interoperable and Reusable (FAIR) data

  • 1. Findable, Accessible, Interoperable, and Reusable (FAIR) data Kate LeMay Senior Research Data Specialist kate.lemay@ardc.edu.au
  • 4. Australian Funders Open access policies Australian Code for the Responsible Conduct of Research Data management statement required for national competitive grants www.arc.gov.au/policies-strategies/strategy/research- data-management National Statement on Ethical Conduct in Human Research Human Research Ethics Application (HREA)
  • 5. Advantages for researchers • Transparency and reproducibility • Maximises value of investment • Citations and impact • Collaborations • Secure ongoing storage • Ethical obligation (clinical trials) • Publications with data cited more often
  • 6. Data sharing/publication isn’t all ”open data” Five Safes risk management framework Image CCBY http://archive.stats.govt.nz/browse_for_stats/snapshots-of- nz/integrated-data-infrastructure/keep-data-safe.aspx
  • 7. F.A.I.R. data principles • Drafted in a workshop in 2014 • Nature article* and support by FORCE11 • Received international recognition • Technology agnostic • Discipline independent • Both the data and the metadata • Human readable and machine readable Image by Sanja Pundir CC-BY-SA * Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).
  • 8. “FAIR principles provide ‘steps along a path’ toward machine- actionability; adopting, in whole or in part, the FAIR principles, leads the resource along the continuum towards this optimal state.” Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).
  • 9. Findable • Describe your data • Give it a persistent globally unique identifier • Make it findable through discipline specific search routes and generic ones F1. (meta)data are assigned a globally unique and eternally persistent identifier. F2. data are described with rich metadata. F3. (meta)data are registered or indexed in a searchable resource. F4. metadata specify the data identifier.
  • 10. Accessible • Accessibility is a spectrum • Deposit in repository • If not open, provide information how the researcher can get access to the data and background information (e.g. codebooks, methods, software, algorithms) A1 (meta)data are retrievable by their identifier using a standardized communications protocol. A1.1 the protocol is open, free, and universally implementable. A1.2 the protocol allows for an authentication and authorization procedure, where necessary. A2 metadata are accessible, even when the data are no longer available. Open Mediated Closed
  • 11. Interoperable • Use a standard file format • Use a community agreed vocabulary (MeSH, SNOMED CT, ICD-10…) • Link to relevant information I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies (and ontologies) that follow FAIR principles. I3. (meta)data include qualified references to other (meta)data.
  • 12. Reusable Other aspects on top of F.A.I. : • Discipline specific information about the output • Information on how the data was created • A machine readable licence (Creative Commons recommended, see our licensing guide ands.org.au/guides/copyright-data-and- licensing) R1. meta(data) have a plurality of accurate and relevant attributes. R1.1. (meta)data are released with a clear and accessible data usage license. R1.2. (meta)data are associated with their provenance. R1.3. (meta)data meet domain-relevant community standards.
  • 13. F.A.I.R resources Icons made by Freepik are licensed by CC BY 3.0 Entire FAIR resources graphic is licensed under a Creative Commons Attribution 4.0 International License ands.org.au/working-with-data/fairdata Self assessment tool
  • 14. Sensitive data resources ands.org.au/working-with-data/sensitive-data Publishing and sharing sensitive data Guide Data sharing considerations for Human Research Ethics Committees Guide De-identification Guide
  • 15. With the exception of third party images or where otherwise indicated, this work is licensed under the Creative Commons Attribution 4.0 International Licence. The ARDC is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program Kate LeMay Senior Research Data Specialist kate.lemay@ardc.edu.au @katelemayardc