Overview of FAIRsharing, principles and metrics; RDA/Force11 activities an adopters - examples in the Agro domain

1. FAIRsharing and the FAIRmetrics
Implementing the FAIR principles in the agricultural domain
Research Data Alliance (RDA) – Plenary 11th, Berlin, 19-23 March, 2018
Slides at: https://www.slideshare.net/SusannaSansone
Associate Professor, Associate Director
Susanna-Assunta Sansone, PhD
ORCiD: 0000-0001-5306-5690
@SusannaASansone
Consultant, Honorary Academic Editor

4. Ready for use, implementation, or recommendation
In development
Status uncertain
Deprecated as subsumed or superseded
All records are manually curated
in-house and verified and claimed by
the community behind each resource
Interlinks, indicators of status, community vetting
Databases/data
repositories
Metadata standards
Formats Terminologies Guidelines
Data policies by
funders, journals and
other organizations

5. Example of agro-relevant records

11. • Harvesting AgroPortal ontologies and vocabularies into FAIRsharing
o Manually curate the metadata, better synchronization of the fields
o AgroPortal has a brand new metadata model of 127 properties to describe ontologies
& vocabularies
§ RDA Vocabulary and Semantic Services IG has now an ontology metadata task group
Ongoing work
Clement Jonquet

14. • Top recommended databases are all repositories, as expected
• Outliers are knowledgebases such as model organism data resources, such as
FlyBase
Work in progress
Data resources recommended by publishers/journals

15. Other indicators for data resources:
community evaluations,
stakeholders criteria,
certifications,
and metrics of FAIRness
(work in progress)

16. In scope:
• A shared list of recommended deposition
repositories to save editors/publishers time and
provide authors with a consistent guidance
• focus on repositories accepting submission
Out of scope:
• Become or compete with
• a certification for repositories, like the
recently launched CoreTrustSeal (CTS:
Data Seal of Approval & World Data
System initiatives)
• evaluation by a community authority in a
given area, e.g. by ELIXIR
Force11 DCIP and FAIRsharing – ongoing discussion

17. Objectives:
1. Ensure that FAIRsharing will provide a
means by which repository certifications
(e.g. CTS) and/or community-driven
evaluations (e.g. ELIXIR) can be used to
display, filter and search for repository
discovery
1. Review existing recommendations by
publishers/journals’ to identify common set
of criteria (currently used) for selecting
repositories
Force11 DCIP and FAIRsharing – ongoing discussion

18. in review at
Proposed metrics and framework
The FAIRmetrics.org
Working Group:
a core set of semi-quantitative
metrics (measurable indicators)
for the evaluation of FAIRness
FAIRmetrics.org
https://github.com/FAIRMetrics
FAIRness reflects the extent to which a digital resource addresses
the FAIR principles as per the expectations defined by a community

19. • We are working with the FAIR metrics WG to:
• Serve as registry to describe digital assets (databases/repositories, standards,
policies), enhance discoverability (schema.org), citability (DOIs)
• Be a look up service for identifier schemas and standards
• Engage with journals and publishers on their needs and use of the metrics
Varsha K, Iain H, Andrew H = Springer Nature
Emma G = PloS
Theo B = BMJ
Jennifer B = OUP
Scott E = Giga
Amye K = BMC
Rebecca L, Mikael M = F1000
Robert K, DavidC = WT Open Research
Thomas L = EMBO
Helena C = Elsevier
Jonathan T = Ubiquity
Myles A = Nat Gen
Role of FAIRsharing
in review at
FAIRmetrics.org
https://github.com/FAIRMetrics

20. rd-alliance.org
known as the BioSharing WG
known as the FAIRsharing WG

21. Access this document from the RDA BioSharing WG or the Force11 FAIRsharing WG pages, or click here

22. 1. The FAIRsharing registry of curated and interlinked records on
o standards (for identifying, reporting, and citing data and metadata),
o databases (repositories and knowledge-bases) and
o data policies (from journals, publishers, funders and other
organizations)
2. The related FAIRsharing recommendations
o to guide users and the producers of standards and databases to select
and describe these resources, or to recommend them in data policies

25. Examples of use and adoption

28. http://blogs.plos.org/everyone/2018/03/01/criteria-for-recommended-data-repositories/

29. Philippe
Rocca-Serra, PhD
Senior Research Lecturer
Alejandra
Gonzalez-Beltran, PhD
Research Lecturer
Milo
Thurston, DPhD
Research Software Engineer
Massimiliano
Izzo, PhD
Research Software Engineer
Peter
McQuilton, PhD
Knowledge Engineer
Allyson
Lister, PhD
Knowledge Engineer
David
Johnson, PhD
Research Software Engineer
Melanie
Adekale, PhD
Biocurator Contractor
Delphine
Dauga, PhD
Biocurator Contractor
Susanna-Assunta Sansone, PhD
Associate Professor, Associate Director
Research Software Engineer
Research Software Engineer
contact@fairsharing.org
@FAIRsharing_org
fairsharing.org/communities