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FAIRness of training materials
Ellen Leenarts, DANS
Based on the work done in WP7 by:
Eileen Kühn, KIT
Angus White, DCC
Rahul Thorat, DANS
www.dans.knaw.nl
The EOSC as a ‘skills commons’ providing FAIR training for FAIR data
stewardship – A workshop organised by EOSCpilot WP7, at the EUDAT
Conference Putting the EOSC Vision in Practice, Porto, 25 January 2017
FAIR data principles for training
materials and events
Why make training materials – FAIR?
Findable
Accessible
Interoperable
Reusable
2
Target audiences
EOSC users: find most relevant training materials and events
EOSC trainers: find, reuse and attribute materials, scale up
number of training events
EOSC TaaS : provide a comprehensive collection of training
materials and events with regards to the EOSCpilot Competence
Framework and EOSC service portfolio
www.eoscp The European Open Science Cloud for Research 3
Findable
F1 (meta)data are assigned a globally unique and persistent
identifier
Repositories offering DOIs and versioning
F2 data are described with rich metadata
F3 (meta) data clearly and explicitly include the identifier of
the data it describes
F4 (meta)data are registered or indexed in a searchable
resource
e.g. TeSS - Elixir
4
Accessible
A1 (meta)data are retrievable by their identifier using a standardized
communications protocol
Eg. Repository harvesting protocols OAI-PMH and ResourceSync
Authentication and authorization procedure for the protocol
A2 metadata are accessible, even when the data are no longer available
Additional: Data in as many formats as feasible (e.g. pdf and txt)
5
Interoperable
I1: (meta)data use a formal, accessible, shared, and broadly
applicable language for knowledge representation.
Commonly supported formats
I2: (meta)data use vocabularies that follow FAIR principles
I3: (meta)data include qualified references to other (meta)data
6
Reusable
R1meta(data) are richly described with a plurality
of accurate and relevant attribute
Licenses e.g. creative commons, open preferred
Detailed provenance
Domain-relevant community standards
7
What next – poll and break out!
Join our group: How can EOSC support research training providers to
contribute to international level training infrastructure?
Should FAIR principles be extended to training resources, and if so what kinds
of resources are worth the effort to make reusable?
Should EOSC perform quality assurance, certification of providers, or badging
of content in a central catalogue of training materials and events harvested
from participating organisations?
Should EOSC monitor what is being provided and attempt to fill gaps either in
the content or mode of delivery?
www.eoscp The European Open Science Cloud for Research 8
EOSC pilot poll
www.eoscp The European Open Science Cloud for Research 9
EOSC pilot poll
www.eoscp The European Open Science Cloud for Research 9

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FAIRness of training materials

  • 1. FAIRness of training materials Ellen Leenarts, DANS Based on the work done in WP7 by: Eileen Kühn, KIT Angus White, DCC Rahul Thorat, DANS www.dans.knaw.nl The EOSC as a ‘skills commons’ providing FAIR training for FAIR data stewardship – A workshop organised by EOSCpilot WP7, at the EUDAT Conference Putting the EOSC Vision in Practice, Porto, 25 January 2017
  • 2. FAIR data principles for training materials and events Why make training materials – FAIR? Findable Accessible Interoperable Reusable 2
  • 3. Target audiences EOSC users: find most relevant training materials and events EOSC trainers: find, reuse and attribute materials, scale up number of training events EOSC TaaS : provide a comprehensive collection of training materials and events with regards to the EOSCpilot Competence Framework and EOSC service portfolio www.eoscp The European Open Science Cloud for Research 3
  • 4. Findable F1 (meta)data are assigned a globally unique and persistent identifier Repositories offering DOIs and versioning F2 data are described with rich metadata F3 (meta) data clearly and explicitly include the identifier of the data it describes F4 (meta)data are registered or indexed in a searchable resource e.g. TeSS - Elixir 4
  • 5. Accessible A1 (meta)data are retrievable by their identifier using a standardized communications protocol Eg. Repository harvesting protocols OAI-PMH and ResourceSync Authentication and authorization procedure for the protocol A2 metadata are accessible, even when the data are no longer available Additional: Data in as many formats as feasible (e.g. pdf and txt) 5
  • 6. Interoperable I1: (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. Commonly supported formats I2: (meta)data use vocabularies that follow FAIR principles I3: (meta)data include qualified references to other (meta)data 6
  • 7. Reusable R1meta(data) are richly described with a plurality of accurate and relevant attribute Licenses e.g. creative commons, open preferred Detailed provenance Domain-relevant community standards 7
  • 8. What next – poll and break out! Join our group: How can EOSC support research training providers to contribute to international level training infrastructure? Should FAIR principles be extended to training resources, and if so what kinds of resources are worth the effort to make reusable? Should EOSC perform quality assurance, certification of providers, or badging of content in a central catalogue of training materials and events harvested from participating organisations? Should EOSC monitor what is being provided and attempt to fill gaps either in the content or mode of delivery? www.eoscp The European Open Science Cloud for Research 8
  • 9. EOSC pilot poll www.eoscp The European Open Science Cloud for Research 9
  • 10. EOSC pilot poll www.eoscp The European Open Science Cloud for Research 9