A 15 minute talk presented at the ELIXIR Europe/ELIXIR UK SME Forum at Churchill College in Cambridge, UK in January 2018. This talk reviews the work our group does in relation to the FAIR principles as part of ELIXIR and beyond.

1. FAIR landscape in ELIXIR:
FAIR metrics and other
initiatives
Peter McQuilton, PhD
FAIRsharing.org & ISA-tools.org
ELIXIR SME Forum, Cambridge UK, January 2018

2. 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

3. These put emphasis on enhancing the
ability of machines to automatically find
and use the data, in addition to supporting
its reuse by individuals

4. • Not always well cited, stored
oSoftware, code, workflows are hard to find/access
• Poorly described for third party reuse
oDifferent levels of detail and annotation
• Curation activities are perceived as time-consuming
oCollection and harmonization of detailed methods and
experimental steps is rushed at the publication stage
Lots of data isn’t FAIR – low findability and badly documented

5. • 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
We need more FAIR
To do better science, more efficiently, we need data that are…

6. Wider adoption of the FAIR principles, by research infrastructure
programmes, e.g.

8. Metadata for data discovery – making data FAIR
DataMed – biomedical data search
engine, based on DATS
DATS – core set of elements
applicable to any dataset

9. scscscsc/BioSchemas/specifications/tree/master/DataCatalog
Surfacing metadata on data repositories, datasets,
training materials and more

10. 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
Making Standards, Databases and Policies FAIR
Talk in session 3 - 18:30 today

11. Content standards
Models/Formats = Conceptual model,
conceptual schema, exchange
formats
Terminologies = Controlled
vocabularies, taxonomies,
thesauri, ontologies etc.
Guidelines = Minimum information
reporting requirements, checklists
Formats Terminologies Guidelines
Initial focus on metadata (or content) standards

12. Formats Terminologies Guidelines
240+
119+
709+
Source:
Sources:
MIAME
MIRIAM
MIQAS
MIX
MIGEN
ARRIVE
MIAPE
MIASE
MIQE
MISFISHIE….
REMARK
CONSORT
SRAxml
SOFT FASTA
DICOM
MzML
SBRML
SEDML…
GELML
ISA
CML
MITAB
AAO
CHEBIOBI
PATO ENVO
MOD
BTO
IDO…
TEDDY
PRO
XAO
DO
VO
~1500
Source:
FAIRsharing enhances their findability

13. Content standards
Data policies by
funders, journals and
other organizations
Databases/Repositories
Formats Terminologies Guidelines
Mapping a complex and evolving landscape

14. 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

17. Curated and maintained, linked metadata records

18. https://doi.org/10.1101/245183

19. bsg-000174
biosharing:
ReportingGuideline
bsg-000161
MINSEQE
MIMARKS
sample
information
sample
identifier
taxonomy
identifier
sequence
read
geo location
High-level information about the
metadata standards
Representations
of the standards elements
Template elements for
el-000001
el-000002
el-000003
provenance:
MINSEQE
provenance:
MINSEQE
and
MIMARKS
provenance:
MIMARKS
• Serve machine-readable content metadata standards, providing provenance for their elements
• Inform the creation of metadata templates, rendering standards invisible to researchers
Going one step further – modularise and combine standards

20. 1. (type of use) How do you foreseen using (implementing or recommending) these metrics/indicator? E.g. in the
review process, or an added value filter/badge for your articles or products and services?
2. (type of process) In which form should the metrics/indicators be made available (to you) and what the assessment
process should be (from your prospective)? E.g. in form of a checklist for self-assessment to be used by the
maintainer of the digital resources, and/or should the assessment be made by one (or more) authority, and/or
crowd-sourced?
2.1. Any preference on who the authority should be (e.g. a self-appointed group or a formal organization)?
3. (level of technicality) If the metrics/indicators were made available in both as human-readable form (e.g. a
form/checklist to fill) and machine-readable form (automate the assessment process), do you have a preference or
priority?
4. (current practices) Are there metrics/indicators for repositories you are considering to use or recommend, such e.g.
data seal of approval or ISO16363? If yes, any positive or negative experience you may have that you can share with
me?
5. Are there any specific do or don'ts you want us to consider, and/or a preferences on how we should name things
(e.g. metrics vs indicators)
GO FAIR metrics mini-survey with publishers on prospective FAIR
metrics
FAIRmetrics and FAIRsharing

21. • Survey results will inform FAIRmetrics
• These will draw on metadata from FAIRsharing
• Metrics will be displayed on FAIRsharing
FAIRmetrics and FAIRsharing
Journal, publishers: GO FAIR metrics
Website: FAIRmetrics.org
Paper: https://doi.org/10.1101/225490

22. • These FAIRmetrics (and others) will be
displayed on FAIRsharing for each
resource
FAIRmetrics and FAIRsharing

23. 5:30-6:30pm today
5:30-6:30pm today
5:30-6:30pm today
9:50am tomorrow
ELIXIR is FAIR

24. 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
Project Coordinator/Engineer
Allyson
Lister, PhD
Knowledge Engineer
Eamonn
Maguire, DPhil
Contractor
David
Johnson, DPhil
Research Software Engineer
Melanie
Adekale, PhD
Biocurator Contractor
Delphine
Dauga, PhD
Biocurator Contractor
We work with and for
Susanna-Assunta Sansone, PhD
Associate Professor, Associate Director
and Consultant for Springer Nature
to make data and other digital research outputs
Want to join our team? Two
developer/engineering positions
available.
https://tinyurl.com/FAIRoxford