Presentation given in the "Preparing to deliver FAIR policy engagement and skills using RISE" workshop at IDCC 2020 in Dublin on 17th February 2020

1. Why institutions need to
raise their capabilities
Sarah Jones
Digital Curation Centre
sarah.jones@glasgow.ac.uk
Twitter: @sjDCC
Preparing to deliver FAIR policy engagement and skills using RISE
IDCC workshop, Monday 17th February 2020

2. FAIR – the new buzz word
Image Israel Palacio https://unsplash.com/photos/P6FgiDNe6W4

3. What is FAIR?
A set of principles that describe the attributes
data need to have to enable and enhance reuse,
by humans and machines
Image CC-BY-SA by SangyaPundir

4. Increasing adoption by funders

5. provide recommendations on the implementation of FAIR,
including corresponding requirements for EOSC services, in
order to foster cross-disciplinary interoperability
EOSCsecretariat webinar, 1st July 2019 5
HOW
1. Data standards & sharing agreements
2. Upscale best-practice solutions
3. EOSC Interoperability Framework
4. Identify service requirements for FAIR
5. Persistent Identifier Policy for EOSC
6. Frameworks to assess FAIR data and
certify services that enable FAIR
7. Converge towards globally-accepted frameworks
WHAT WHY
Q1 2020
2020 Annual
FAIR work plan
Q4 2019
PID policy defined
Outline metrics for
FAIR data & service
certification
Q3 2020
EOSC
Interoperability
Framework
Q2 2019
2019 Annual
FAIR work plan
Q4 2020
Updated PID policy
Updated FAIR metrics
& service certification
testing & iterating
Connect people,
data and service
via standards
Be the glue
Chair: Sarah Jones

6. FAIR Data Expert Group
Take a holistic approach to lay out what needs to be done to
make FAIR a reality, in general and for EOSC
Addresses the following key areas:
1. Concepts for FAIR
2. Creating a FAIR culture
3. Creating a technical ecosystem for FAIR
4. Skills and capacity building
5. Incentives and metrics
6. Investment and sustainability
Turning FAIR into Reality: Report and Action Plan
https://doi.org/10.2777/1524

7. Address culture and technology
Incentives
Metrics
Skills
Investment
Cultural and
social aspects
that drive the
ecosystem and
enact change
Policies
DMPs
Identifiers
Standards
Repositories
Cloudofregistries
Two sides of one whole

8. FAIR Digital Objects
8

9. How do we implement FAIR?
Image Alex Knight https://unsplash.com/photos/2EJCSULRwC8

10. What FAIR means: 15 principles
Findable
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.
Interoperable
I1. (meta)data use a formal, accessible, shared, and
broadly applicable language for knowledge
representation.
I2. (meta)data use vocabularies that follow FAIR
principles.
I3. (meta)data include qualified references to other
(meta)data.
Accessible
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.
Reusable
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.
Slide CC-BY by Erik Schultes, Leiden UMC
doi: 10.1038/sdata.2016.18

11. Joint responsibilities
Principle Researcher role Service role
F1. Assign a PID Choose a relevant service Assign PIDs
F2. Rich metadata Create appropriate metadata Link data and metadata
F3. Indexed, searchable resource Choose a relevant service Ensure metadata search
F4. Metadata specify PID Choose a relevant service Link metadata and PID
A1. Standard protocol for retrieval Choose a relevant service Use standard protocols
A1.1 Open, free protocol Choose a relevant service Use open, free protocols
A1.2 Authenticated access if needed Choose a relevant service Provide authenticated access
A2. Metadata remain accessible Choose a relevant service Provide tombstone records
I1. Use of formal language (standards) Adopt standards Support appropriate standards
I2. Metadata vocabularies are FAIR Advocate for FAIR metadata Support FAIR metadata
I3. Qualified references (linked data) Cross-reference resources Cross-reference resources
R1. Rich metadata (plurality of attributes) Enrich metadata/documentation Advocate for good metadata
R1.1 Clear data usage licence Choose appropriate licence Require licences
R1.2 Metadata covers provenance Say where data came from Require provenance
R1.3 Community standards Adopt community standards Support community standards
Equal, if not more, responsibility on data services

12. Researcher role
1. Adopt relevant standards as you create data
2. Create rich metadata and documentation which
• conforms to community standards
• explains provenance
• assigns a clear usage licence
• cross-links data, metadata, code and other resources
3. Choose appropriate data services which
• assign Persistent Identifiers
• enhance discoverability via indexes / catalogues
• use standard protocols for (authenticated) access
4. Advocate for / contribute to community standards

13. Institutional role
1. Raise awareness of community standards
2. Help researcher select appropriate data services
3. If running a repository:
• assign Persistent Identifiers
• ensure metadata specifies the PID
• expose metadata via indexes / catalogues / harvesting…
• use standard protocols for (authenticated) access
• cross-reference resources
• keep metadata accessible, even when data aren’t
4. Set requirements / advocate for good practice

14. Inherent link: data and services
In order for data to be FAIR,
you need services that enable FAIR