Update given to the Research Data Alliance Plenary 12 joint meeting session: WG FAIRSharing Registry and Data Policy Standardisation and Implementation IG, on Monday 5th November 2018, Gaborone, Botswana

1. Data Policy Standardisation
and Implementation IG
Varsha Khodiyar, PhD
RDA P12 , 5th Nov 2018
IllustrationinspiredbytheworkofAlfredNobel

2. 1
Current landscape of publisher research data policies
• Springer Nature: Four policies – Type 1 to Type 4 with additional
requirements for life sciences journals. 2016

3. 2
Data policy standardisation and implementation IG est 2016
https://www.rd-alliance.org/groups/data-policy-standardisation-and-implementation
Co-chairs:
Natasha Simons (ARDC), Simon Goudie
(Wiley), Azhar Hussain (Jisc), Iain
Hrynaszkiewicz (Springer Nature)
Primary objective is to help define
common frameworks for research data
policy – starting with journals and
publishers and latterly funding agencies

4. 3
Current landscape of publisher research data policies
• Springer Nature: 2016 Four policies – Type 1 to Type 4 with additional
requirements for life sciences journals.
• Elsevier: 2017 Five options – A-E, from encouraging research data
deposit and citation to requiring data deposit, data citation and data
peer review
• Wiley: 2017 Three policies – Encourages Data Sharing, Expects Data
Sharing, Mandates Data Sharing.
• Taylor & Francis: 2018 Four policies – Basic, Share on Reasonable
Request, Publicly Available, Open Data and Open and Fully FAIR.

5. 4
Journal and publisher research data policy DRAFT
framework
https://docs.google.com/document/d/1DTAfOKkE1a2n2f_1hGcrXlrw-5Tq_AL5tk-ju8B82_E
An increasing number of publishers and journals are implementing policies that require or
recommend published articles to be accompanied by the underlying research data. These
policies are an important part of the shift toward reproducible research and contribute to
the availability of research data for reuse.
While uptake of journal data policies is on the rise, there is wide variation between
policies…difficult for researchers in understanding and complying with data policies, and
complex for infrastructure providers and research support staff to assist data policy
compliance. There is clear benefit in a more standardised approach, as evidenced in the
findings of the Jisc UK Journal Data Registry Project and the pioneering work of publishers
such as Springer Nature to develop and support standard policy types for their journals.
This draft framework is intended to help Journal Editors to navigate the creation or
enhancement of a data availability policy. It reflects international efforts by the Research
Data Alliance Data Policy Standardisation and Implementation Interest Group to identify the
key elements of a good data availability policy and to standardise data policies.

6. 5
Features 1 to 4
Feature What and why How (implementation)
Definition of
research data
Define which research data
the policy applies to
Define research data as being the data
that support the findings or claims
made in the published article.
Definition of
exceptions
Acknowledge legitimate
exceptions
Define sensitive data
Embargoes Define if and what
embargoes on data release
are permitted
Include a positional statement on
embargoes
Supplementary
materials
Define the position on data
sharing via supplementary
material
Specify if sharing via supplementary
materials is permitted but data sharing
via repositories must be preferred
wherever possible.

7. 6
Features 5 to 8
Feature What and why How (implementation)
Data repositories State position on use of data
repositories
Must be supported with list of
recommended, trusted or supported
data repositories
Data citation Statement on support for
persistent identifiers
Specify that data citation is permitted
and provide style guide for referencing
data
Data licensing Define position on licensing
and copyright for research
data
Specify permitted data licenses
Researcher/ author
support
Research data sharing
remains a new concept for
some journals and
disciplines
Provide details for an individual or
team, that authors can contact with
questions on research data policy
compliance and data sharing in
general

8. 7
Features 9 to 12
Feature What and why How (implementation)
Data availability
statements (DASs)
Define position on provision of
DASs
Include definition of a DAS, advice
on enforcement, and guidance on
placement within manuscript.
Mandatory data
sharing (specific
papers)
Statement on whether data
sharing is mandatory for specific
types of research data
Specify any data sharing mandates
that are a condition of submission
and/or publication. Provide advice
on mechanisms for compliance.
Data formats and
standards
State position on the use of
community/discipline specific
data standards
Provide a statement in support of
community standards. Note
minimal reporting standards are
NOT included in this policy.
Mandatory data
sharing (all papers)
Sharing of research data via
repositories or supplementary
information is required on or
publication for all articles
For these journals “available on
request” DASs are not acceptable.
Provide advice on mechanisms for
compliance.

9. 8
Features 12 to 15
Feature What and why How (implementation)
Mandatory data
citation
To ensure consistent linking of
important research outputs to
published articles
State requirements for authors
to formally reference any
publicly-available data on
which the conclusions of the
paper rely
Peer review of
data
Where data are made available
with research articles they are
accessible to peer reviewers. For
journals with a strong focus on
data peer review of the data can
be required.
Statement on whether peer
review of data is expected or
required
Data Management
Plans (DMPs)
Analogous to medical journals
encouraging sharing or
publication of study protocols.
Define if DMPs are encouraged
or required to be shared under
the research data policy.

10. 9
Policy levels - features 1 to 9
Feature Policy 1 Policy 2 Policy 3 Policy 4 Policy 5 Policy 6
Definition of the research
data
● ● ● ● ● ●
Definition of exceptions ● ● ● ● ● ●
Embargoes ● ● ● ● ● ●
Supplementary materials ● ● ● ● ● ●
Data repositories ● ● ● ● ● ●
Data citation ● ● ● ● ● ●
Data licensing ● ● ● ● ● ●
Researcher/ author
support
◐ ● ● ● ● ●
Data availability
statements
○ ◐ ● ● ● ●
○ ◐ ●
Not required May be required/
encouraged
Required and enforced

11. 10
Policy levels - features 10 to 15
Feature Policy 1 Policy 2 Policy 3 Policy 4 Policy 5 Policy 6
Mandatory data sharing
(specific papers)
○ ◐ ◐ ● ● ●
Data formats and
standards
○ ◐ ◐ ◐ ◐ ●
Mandatory data sharing
(all papers)
○ ○ ◐ ◐ ● ●
Mandatory data citation ○ ○ ◐ ◐ ◐ ●
Peer review of data ○ ○ ◐ ◐ ◐ ●
Data Management Plans
(DMPs)
○ ○ ◐ ◐ ◐ ●
○ ◐ ●
Not required May be required/
encouraged
Required and enforced

12. 11
Comments or feedback on the draft policy framework?
Key issues being addressed in revision of framework
• Improve clarity around when an implementation action is simply to
provide information, and when implementation requires a new
check by editors, reviewers or publishers, or action by an author
• Better define the scope e.g. the document will not define criteria for
trusted data repositories or provide detailed guidance on data
availability statements (other projects are working on these)
• Getting the balance between pragmatism and immediate practical
use, and aspiration (e.g. DMP requirements, supplementary
information files)
• Your comments?

13. 12
Next steps for the data policy standardisation and
implementation IG
• Nov-Dec 2018: Complete revision, in light of community comments, of
Master Policy framework
• Jan-Mar 2019: Release revision for community comment
• Apr 2019: Present final draft at RDA Plenary
• April 2019 –
• Increase publisher, funder, institution and editor engagement
• Implementation of framework at first journals/publishers
• Submit framework for peer reviewed publication
• Explore other adoption, implementation and outreach activities e.g.
• Assessment tools for journals and publishers
• Case studies
• Impact (cost and benefit) analyses
• Open to suggestions..!

14. 1313
The story behind the image
Alfred Nobel (1833–1896)
Alfred Nobel was a Swedish chemist, engineer and inventor
of dynamite. Dynamite made him very wealthy but partly
in response to concerns about its negative uses, he decided
to give the vast majority of his estate to establish the four
Nobel Prizes with a fifth awarded in his memory, to people
or organisations who promote peace around the world.
Thank you
Varsha.Khodiyar@nature.com
@varsha_khodiyar
Presented on behalf of
Iain Hrynaszkiewicz
Head of Data Publishing
Iain.Hrynaszkiewicz@nature.com