Presentation at the Open Science FAIR. Porto Sept. 16-18, 2019.

1. Enabling FAIR: what works?
Bottom up
Susanna-Assunta Sansone
ORCiD: 0000-0001-5306-5690 | Twitter: @SusannaASansone
Fostering a FAIR research culture - what works | Open Science FAIR, Porto, Portugal, 16-18 September 2019
Slides: https://www.slideshare.net/SusannaSansone
sansonegroup.eng.ox.ac.uk
Associate Professor, Engineering Science
Associate Director, Oxford e-Research Centre
Principal Investigator and Group Leader

2. €3.3 billion
programme
2014 - 2020
€300 million
programme
2018 - 2020
European
intergovernmental
organisation
23 member
countries and
over 180 research
organisations
Since 2014
1
2
3 Started in 2019
FAIR-enabling EU and USA biomedical infrastructure
programmes and projects, e.g.
Since in 2014, several programs:
2014-2017
2017-2018

3. Organization and structure
• Hub and (national) Nodes
• Community-driven and rooted
• Strong focus on interoperability
• SMEs and Industry links
• Cross-nodes funded activities

4. Academics from several ELIXIR Nodes, with Janssen, AstraZeneca, Eli Lilly,
GSK, Novartis, Bayer, Boehringer Ingelheim
Define and implement a data FAIRification process and infrastructure:

5. Working structure
• Human capital maximization
• Squads cross-cutting WPs & organizations
• Three months sprint cycles
• Prioritization based on pharma's needs
```
FAIRcookbook

6. Rocca-Serra and Sansone: 10.5281/zenodo.3274256
FAIRcookbook
Practical recipes

7. 1 2014-2017
12 centres of excellence
2 2017-2018
3 Started in 2019
10 multi-PIs teams, forming one consortium
around 3 data types/databases
A consortium of 6 teams

8. 1 2014-2017
12 centres of excellence
2 2017-2018
3 Started in 2019
10 multi-PIs teams, forming one consortium
around 3 data types/databases
A consortium of 6 teams

9. 1 2014-2017
Building on previous work
• Learn from positive and
negative outcomes
• Assessment of what did not
work well and why
• NIH centres/officers playing an
active role
• Evolving understanding of what
a FAIR Data Commons is
12 centres of excellence
2 2017-2018
3 Started in 2019
10 multi-PIs teams, forming one consortium
around 3 data types/databases
A consortium of 6 teams

10. Stronger impact in discipline-specific efforts:
• anchored to real use cases
• closer to the (needs of the) practitioners
• realistic on what can really be achieved
but not easier, because e.g. biomedical sciences encompasses several
sub-disciplines, with diverse long-standing norms, tools and standards
Balancing social and technical engineering is an achievement per se:
• work with and form the users to match expectations with promises
• address questions/issues, rather then perform technical duties
• pass evidence-based lessons learned to others, good and bad
Defining success – lessons learned

11. Enabling FAIR: what works?
Top-down
Susanna-Assunta Sansone
ORCiD: 0000-0001-5306-5690 | Twitter: @SusannaASansone
Fostering a FAIR research culture - what works | Open Science FAIR, Porto, Portugal, 16-18 September 2019
Slides: https://www.slideshare.net/SusannaSansone
sansonegroup.eng.ox.ac.uk
Associate Professor, Engineering Science
Associate Director, Oxford e-Research Centre
Principal Investigator and Group Leader

12. Since
2011

13. Researchers in academia,
industry, government
Developers and curators
of resources
Journal publishers or
organizations with data
policy
Research data facilitators,
librarians, trainers
Learned societies, unions
and associations
Funders and data
policy makers
A flagship output (and a WG) of the:
Recommended by funders, e.g.:
Core part of implementation networks in:

14. REPOSITORIES,
databases and
knowledgebases
COMMUNITY STANDARDS
DATA POLICIES
by funders, journals
and other organizations
Inter-linked
descriptions
informative and educational resource

15. REPOSITORIES,
databases and
knowledgebases
COMMUNITY STANDARDS
DATA POLICIES
by funders, journals
and other organizations
Inter-linked
descriptions
informative and educational resource
All records are manually curated
in-house, verified and claimed by the
community behind each resource
Ready for use, implementation, or recommendation
In development
Status uncertain
Deprecated as subsumed or superseded

16. REPOSITORIES,
databases and
knowledgebases
COMMUNITY STANDARDS
DATA POLICIES
by funders, journals
and other organizations
Inter-linked
descriptions
informative and educational resource
We guide consumers to discover, select and use these
resources with confidence
We help producers to make their resources more visible,
more widely adopted and cited

20. https://doi.org/10.1038/s41587-019-0080-8
Open Access CC-BY
69 authors (adopters, collaborators, users)
representing different stakeholder groups
Analysed the data policies by
journals/publishers, and the standards and
repositories they recommend
Working with journal editors and publishers

21. Discrepancy in recommendation across the data policies
• some repositories are named, but very few standards are
• cautious approach due to the wealth of existing resources
Recommendations are often driven by
• the editor’s familiarity with one or more standards, notably
for journals or publishers focusing on specific disciplines
• the engagement with learned societies and researchers
actively supporting and using certain resources
Ø Consensus: FAIRsharing plays a key role in helping editors
to discover and recommend appropriate resources
What have we learned and are doing now

22. “The interactive browser will allow us to discover which databases and standards
are not currently included in our author guidelines, enabling us to regularly
monitor and refine our policies as appropriate, in support of our mission to help
our authors enhance the reproducibility of their work.”
H. Murray. Publishing Editor, F1000Research

23. In scope:
• A shared list of recommended deposition
repositories
Out of scope:
• Become or compete with
• certification systems for repositories, such
as CoreTrustSeal;
• evaluation processes by a community
‘authority’ in a given area, e.g. by ELIXIR
in the life sciences
Collaboration:
Harmonize journals and publishers’ data deposition guidelines
by defining a common set of criteria for repository selection
Document being approved internally by publishers; out before / to be presented at RDA’s 14th Plenary, Helsinki

24. Increase the number and the clarity of journals and funders
data policies by classifying the recommendations these policies contain
to improve their definition and guidance to researchers
Collaboration:
Workplan – phase 1:
Curate and assess their compliance to the Transparency and Openness Promotion
(TOP) guidelines and display the level in FAIRsharing