The document discusses standardizing research data policies across journals. It describes an expert group working to develop templates and guidance for data policies. It also discusses a collaboration to implement the Joint Declaration of Data Citation Principles. The group is working with Springer Nature to help standardize their data policies across journals into four main types. The goal is to improve data sharing, citation and reuse.

1. Standardising Research Data Policies
David Kernohan
Image: dkernohan (cc-by)

2. The story so far…
» Based on a previous investigation we wanted to look at
the viability of a registry service for journal data policies…
»… in future this may complement the information
available via our SHERPA services.
»We convened an expert group with international
representation to support the project.
14/09/2016 Jisc Journal Research Data Policy Registry

3. The story so far…
» ”The prototype that could be built would not be an authoritative source of
information for researchers or support staff as it would not contain the
information required at the level of data type […]To answer the question set
using the sources available, a high degree of subjectivity and interpretation
had to be applied as there were very few standard terms or definitions.
Interpretation of policy was often best undertaken at the domain level, which
further compounded the problems of building a scalable, generic database to
codify the information.”
(Naughton and Kernohan, 2016)
Article in “UKSG Insights”: http://doi.org/10.1629/uksg.28

4. The story so far…
Initial Aim
To develop templates and
guidance for journal
publishers around research
data policies
Long-term aim
To revisit the idea of a policy
registry, including an
investigation of the potential
for machine-readable licence
based solutions

5. Collaboration
»Linked to ongoing NIH-supported
BioCaddie project, hosted by the
Force11 Collaboration
»Aimed at developing an
implementation pathway for the
JDDCP principles…
The Data Citation Implementation Pilot (DCIP)
14/09/2016 Jisc Journal Research Data Policy Registry

6. The Joint Declaration of Data Citation Principles (JDDCP)
1. Importance Data should be considered legitimate, citable
products of research. Data citations should be accorded the same
importance in the scholarly record as citations of other research
objects, such as publications
2. Credit and Attribution Data citations should facilitate
giving scholarly credit and normative and legal attribution to all
contributors to the data, recognizing that a single style or mechanism
of attribution may not be applicable to all data.
3. Evidence In scholarly literature, whenever and wherever a
claim relies upon data, the corresponding data should be cited
4. Unique Identification A data citation should include a
persistent method for identification that is machine actionable,
globally unique, and widely used by a community
5. Access Data citations should facilitate access to the data
themselves and to such associated metadata, documentation, code,
and other materials, as are necessary for both humans and machines
to make informed use of the referenced data
6. Persistence
Unique identifiers, and metadata describing the data, and its
disposition, should persist -- even beyond the lifespan of the data
they describe
7. Specificity andVerifiability
Data citations should facilitate identification of, access to, and
verification of the specific data that support a claim. Citations or
citation metadata should include information about provenance and
fixity sufficient to facilitate verfiying that the specific timeslice,
version and/or granular portion of data retrieved subsequently is the
same as was originally cited
8. Interoperability and Flexibility
Data citation methods should be sufficiently flexible to accommodate
the variant practices among communities, but should not differ so
much that they compromise interoperability of data citation practices
across communities
https://www.force11.org/group/joint-declaration-data-citation-
principles-final
(Martone (ed), 2014)
14/09/2016 Jisc Journal Research Data Policy Registry

7. The work of the DCIP
» Five “expert groups”
› EG1: FAQs/Documentation – developing documentation/guidance aimed at
publishers
› EG2: Identifiers
› EG3: Publisher Early Adopters– mapping the publication process as it pertains
to data.
› EG4: Repository Early Adopters – focus on machine readable landing pages
and metadata sharing
› EG5: JATS (Journal ArticleTag Suite)
14/09/2016 Jisc Journal Research Data Policy Registry

8. Publisher early adopters group
14/09/2016 Jisc Journal Research Data Policy Registry
Suite of standardised
policy summaries?
Display data availability
statement?
Data capture
improvements?
Correct XML/JATS
tagging?
Consistent [data] tag?
Author guidance & clear
policiesAuthor submission
Review
Production
Publication
Editorial guidance
Reviewer guidance
Standardised mark-up
and formatting
Clear, consistent display
in pdf and html versions
Data availability to
reviewers?

9. Towards policy standardisation
Springer Nature Data PolicyTypes
14/09/2016 Jisc Journal Research Data Policy Registry
PolicyType Policy Summary Example Journal
Type 1 Data sharing and data citation is
encouraged.
Photosynthesis Research
(Instructions for Authors)
Type 2 Data sharing and evidence of
data sharing encouraged.
Plant and Soil
(Instructions for Authors)
Type 3 Data sharing encouraged and
statements of data availability
required.
PalgraveCommunications
(Editorial policies)
Type 4 Data sharing, evidence of data
sharing and peer review of data
required.
Scientific Data
(Data policies)
From: http://www.springernature.com/gp/group/data-policy/policy-types

10. The Springer Approach (1)
» Goal is to eventually see all 3,000+ Springer Nature
journals conform to one of the four data policy types.
» Currently 350 journals, aiming at 1,000 by the end of
2016.
» Slow, journal-specific process in collaboration with
editorial teams. Started with “easy” journals where there
is already interest in data.
(source: informal discussion with Iain H at Springer)
14/09/2016 Jisc Journal Research Data Policy Registry

11. The springer approach (2)
14/09/2016 Jisc Journal Research Data Policy Registry
Encourage data sharing via
public repository
List of repositories
Advice and support
1
Sharing with researchers
required
Availability statement
encouraged
Public sharing
recommended
List of repositories
Advice and support
2 Sharing with researchers
required
Availability statement
required
Public sharing
recommended
List of repositories
Advice and support
3
Public sharing required
Availability statement
required
Public sharing
recommended
Data included in peer
review
List of repositories
Advice and support
4

12. The springer approach (3)
» Based on Scientific Data journal list.
» “In general, data should be submitted to discipline-
specific, community-recognised repositories where
possible, or to generalist repositories if no suitable
community resource is available”
»Available on figshare for reuse with attribution:
https://figshare.com/articles/Scientific_Data_recommended_repositories_June_2015/1434640
The standard list of repositories
14/09/2016 Jisc Journal Research Data Policy Registry

13. Key questions
» Does this approach help you? (as a research manager/
researcher/ information professional)
»What other information would you need to quickly
understand the requirements of a given journal?
» Are there other ideas that we should be considering?
For discussion:
14/09/2016 Jisc Journal Research Data Policy Registry

14. Follow the project
» blog: https://journalrdregistry.jiscinvolve.org
» webpage: http://www.jisc.ac.uk/rd/projects/journal-research-data-policy-registry-pilot
(all images fromWikipedia page on the Julia Set: https://en.wikipedia.org/wiki/Julia_set )