A 30 minute presentation on FAIRsharing given at the International Workshop on Sharing, Citation and Publication of
Scientific Data across Disciplines in Tachikawa, Tokyo, Japan on Tuesday 5th December, 2017
FAIRsharing Keynote - International Workshop on Sharing, Citation and Publication of Scientific Data across Disciplines
1. Describing and Connecting Standards, Databases and
Policies Across Disciplines
Peter McQuilton, PhD
@fairsharing_org
International Workshop on Sharing, Citation and Publication of Scientific Data across Disciplines,
Tachikawa, Tokyo, 5-7 December 2017
4. A set of principles, for those wishing to enhance
the value of their
data holdings
Designed and endorsed by a diverse set of stakeholders - representing academia, industry, funding
agencies, and scholarly publishers.
9. • Not always well cited, stored
o Software, code, workflows are hard to find/access
• Poorly described for third party reuse
o Different level of detail and annotation
• Curation activities are perceived as time-consuming
o Collection and harmonization of detailed methods and
experimental steps is rushed at the publication stage
Not FAIR – low findability and
badly documented
10. • Available in a public repository
• Findable through some sort of search facility
• Retrievable in a standard format
• Self-described so that third parties can make sense of it
• Intended to outlive the experiment for which they were collected
To do better science, more efficiently,
we need data that are…
11. My database is going
offline, where should I
put the data, and in
what format?
Before accepting my
paper, this journal
wants my data to be in
a public repository, but
which one?
My funder says I
should deposit the
data in a reputable
repository. But
which one?
I’m collecting in-
vivo animal
testing data –
what metadata
should I curate?
I’m about to start a set of
experiments. In what
format should I record
the data?
12. A web-based, curated, and searchable portal that monitors the
development and evolution of standards*, across all disciplines,
inter-related to databases/repositories and data policies
* A standard is a formal community specification for reporting, sharing and
citing data, metadata and other digital assets.
15. Content standards
Data policies by
funders, journals and
other organizations
Databases/Repositories
Formats Terminologies Guidelines
Mapping a complex and evolving
landscape
16. 270
48
23
2
97
87 4
204
9 6 8
Paper in preparation,
preliminary information as of July 2017
Ready for use, implementation, or recommendation
In development
Status uncertain
Deprecated as subsumed or superseded
All records are manually curated
in-house and verified by the
community behind each resource
Community verified status indicators
21. Collections group together
one or more types of
resource by domain,
project or organization.
Recommendations are a
core-set of resources that
are selected and
recommended by a funder
or journal data policy.
Grouping the data
24. Making FAIRsharing FAIR -
Interoperability/Accessibility
• Data annotation:
• Users/Maintainers – ORCID
• Organisations – FundRef
• Species – NCBI Taxon ontology
• Disciplines and Domains – re3data/EDAM/BRO
• API – swagger (ELIXIR guidelines)
• DOIs for standards (coming soon)
25. Making FAIRsharing FAIR -
Findable - Embeddable Widget
• Recommendation/Collection Widget for embedding
in third-party websites
• Journal data policies (GigaScience, PLOS, Springer
Nature…)
• Standard Developing Organisations (e.g. TDWG)
• Societies/Organisations (e.g. ELIXIR)
Dr Massimiliano Izzo
26.
27.
28. Standard developing groups, incl:Journal publishers, incl:
Cross-links, data exchange, incl:
Societies and organisations, incl: Institutional RDM services, incl:
Projects, programmes, incl:
Working with and for the community
OBO