Westminster Higher Education Forum policy conference Open research data in the UK: https://www.westminsterforumprojects.co.uk/conference/open-research-data-20

1. Enabling FAIR
Susanna-Assunta Sansone
ORCiD: 0000-0001-5306-5690 | Twitter: @SusannaASansone
Westminster Higher Education Forum policy conference - Open research data in the UK, 13 February 2020
Slides: https://www.slideshare.net/SusannaSansone
datareadiness.eng.ox.ac.uk
Associate Professor, Engineering Science
Associate Director, Oxford e-Research Centre

2. A set of principles to enhance
the value of all digital
resources
Datasets SOPs Figures, Photos Workflows Slides Codes Tools DatabasesAlgorithmsDocument

3. Findable
Accessible
Interoperable
Reusable
• Globally unique, resolvable, and persistent identifiers
▪ To retrieve and connect data
• Community defined descriptive metadata
▪ To enhance discoverability
• Common terminologies
▪ To use the same term mean the same thing
• Detailed provenance
▪ To contextualize the data and facilitate reproducibility
• Terms of access
▪ Open as possible, closed as necessary
• Terms of use
▪ Clear licences, ideally to enable innovation and reuse
Data for humans and for machines

4. doi.org/10.2777/02999doi.org/10.2777/1524
www.gov.uk/government/publications/open-
research-data-task-force-final-report
doi.org/10.5281/zenodo.1245568
www.ukri.org/research/infrastructure
www.turing.ac.uk/research/impact-
stories/changing-culture-data-science
FAIR is aligning the broad community
around common guidelines
“…we estimate to be 10.2
billion euros per year…”

5. Everybody needs data that are
• Discoverable and usable at scale
• Retrievable and structured in standard format(s)
• Self-described so that third parties can make sense of it
An enabler of the digital transformation
nih-cfde.orgwww.pistoiaalliance.org fairplus-project.eu

6. The scholarly publishing
ecosystem is changing
Data-relates mandates by funders
and institutions are growing
Researchers need
recognition and credit
theconversation.com/how-robots-can-help-us-embrace-a-more-human-view-of-disability-76815
Human-machine collaboration is the future
Responding to needs and crisis
o 21% pharmacology data (doi.org/10.1038/nrd3439-c1)
o 11% cancer data (doi.org/10.1038/483531a)
o unsatisfactory in ML (openreview.net/pdf?id=By4l2PbQ-)
towardsdatascience.com/scientific-data-analysis-pipelines-and-reproducibility-75ff9df5b4c5
Reproducibility of published studies is still problematic

7. Depends upon several stakeholders in the research ecosystem
actively playing their parts to:
• deliver research infrastructures, tools and standards,
policies, education and training
• address technical, social and cultural challenges
Making FAIR a reality

8. The road to FAIRness
Before FAIR
http://blogs.nature.com/scientificdata/2019/10/22/the-layered-cake

9. The road to FAIRness
Before FAIR
After FAIR
http://blogs.nature.com/scientificdata/2019/10/22/the-layered-cake

10. The road to FAIRness
Before FAIR
After FAIR
….from chaos,
comes order?
http://blogs.nature.com/scientificdata/2019/10/22/the-layered-cake

11. COMMUNITY STANDARDS
Inter-linked descriptions
REPOSITORIESDATA POLICIES
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 of and a WG in:
Recommended by funders, e.g.:

12. Working on a set of criteria that journals and
publishers believe are important for the
identification and selection of data
repositories, which can be recommended to
researchers when they are preparing to
publish the data underlying their findings
Participating
publishers:
Data Repository Selection: Criteria That Matter
Pre-print:
https://osf.io/m2bce

13. infrastructures
standards
tools
policies
education
training
cultural normalization
incentives
long term investment
A FAIRy tale needs some magic…
It is not simple, but it is no longer optional