Invited presentation to the Association of Learned and Professional Society Publishers September 2016

1. Peer Reviewing Data: experiences from a data journal
Varsha Khodiyar, PhD
Data Curation Editor, Scientific Data
15.09.2016

2. 1
The data journal

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Scientific Data, a Nature Research journal
Data Descriptor
Primary article type; sound
science and facilitates data
reuse
Analysis
New analyses or meta-
analyses of existing data
Article
Original reports on
advances in data sharing &
reuse
Comment
Announcements of broad
interest; usually invited
www.nature.com/scientificdata

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Under the hood of a Data Descriptor
• Synthesis
• Analysis
• Conclusions
• Context in which the data was
generated (background)
• How was the data generated?
• How was the data processed?
• Where is the data?

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Data Descriptors have human and machine
understandable components
Human readable
representation of
study
i.e. article (HTML &
PDF)
Human readable
representation of
study
i.e. article (HTML &
PDF)

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Data Descriptors have human and machine
understandable components
Machine accessible
representation of
study
i.e. metadata

7. 6
Guidance for authors

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Templates and detailed guidance available online

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Recommended repositories
Browse our recommended data repositories online.
• We currently list more than 80 repositories, across biological,
medical, physical and social sciences
• When required, we provide guidance to authors on the best place
to store their data
nature.com/sdata/policies/repositories

10. 9
The review process

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Editorial office
Susanna-Assunta Sansone
Honorary Academic Editor
Andrew L. Hufton
Managing Editor
Varsha K. Khodiyar
Data Curation Editor

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Selection of Editorial Board members
Experts in their discipline
AND
Demonstrable experience of data standards, data reuse or data
analysis in their discipline
www.nature.com/sdata/about/editorial-board#eb

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Data peer review
www.nature.com/sdata/policies/for-referees
Experimental
Rigor and
Technical Data
Quality
Were data produced in a sound manner?
Technical quality of data – appropriate statistical analyses?
Experimental rigor - appropriate depth, coverage?
Completeness
of the
Description
Sufficient detail to allow others to reproduce these steps?
Sufficient detail to allow others to reuse this data?
Consistent with relevant minimum reporting standards?
Integrity of the
Data Files and
Repository
Record
Do data files appear complete and match manuscript
descriptions?
Are data archived to the most appropriate repository?

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We capture metadata about the dataset being described in each Data Descriptor.
During the metadata curation process
• Manuscript re-read
• Data archive checked
• Minor issues with the data and/or manuscript often identified
Metadata curation and final data checking

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Why a Data Descriptor may be rejected
Reject without review
• Out of scope or no data present
Reject after review
• Serious flaws in the study design, e.g.
lack of crucial controls
• Serious issues identified in the data
files by the peer reviewers
After rejection
• Address concerns and resubmit to Scientific Data
• Resubmit to another data journal
• Withdraw data from Scientific Data integrated repositories
Data should be technically reliable and suitable for use by others

16. 15
Summary

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Data peer review at Scientific Data
Data Archive
• Checked multiple times
• Scientific reasoning underlying
data reviewed by active
researchers
• Technical validity reviewed by
discipline experts
Data Citations
• Citation accuracy confirmed by
specialist editor
• Citation format checked by
editorial team
• Data linkage tested by
production team
Data peer review does not have to be onerous
Reviewing data can save overall reviewing time

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Thank you
Visit nature.com/scientificdata
Email scientificdata@nature.com
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