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Gaining credit for sharing research data: Viewpoints on Data Publishing
1. Gaining credit for sharing research
data
Varsha Khodiyar, PhD
Data Curation Editor, Scientific Data
Nature Publishing Group
varsha.khodiyar@nature.com
@varsha_khodiyar
@scientificdata
Viewpoints on Data Publishing
University of Southampton, 21st September 2015
3. An example Data Descriptor
3
Human
readable
representation
of study
i.e. article
(HTML & PDF)
Human readable
representation
of study
i.e. article
(HTML & PDF)
Machine
readable
representation
of study
i.e. metadata
4. Sections:
• Title
• Abstract
• Background & Summary
• Methods
• Data Records
• Technical Validation
• Usage Notes
• Figures & Tables
• References
• Data Citations
Data Descriptor
Detailed descriptions of the methods and technical analyses
supporting the quality of the measurements.
Does not contain tests of new scientific hypotheses
Article
6. In-house curation team:
• assists users to submit the
structured content via
simple templates and an
internal authoring tool
• performs value-added
semantic annotation of the
experimental metadata
analysis
method
script
Data file or
record in a
database
Data Descriptor
Structured metadata
7. Licences
Data: the primary datasets will reside in
public repositories.
Metadata: released under the CC0 waiver
to maximize reuse and aid data miners
Data Descriptor article: Licensed by
default under the CC BY licence
8. Helping authors
find the right place for their data
Browse our recommended data repositories online.
• We currently list almost 80 repositories, across
biological, medical, physical and social sciences
• When required, we provide guidance to authors on the
best place to store their data
http://www.nature.com/sdata/data-policies/repositories
9. Selecting a repository for your data
Considerations:
1.Is your data Structured or Unstructured?
2.If Structured, is there a repository that
specifically hosts your type of data?
3.If Unstructured (or no structured repository for
your data exists), does your funder or
institution mandate deposition to a particular
repository?
9
11. What makes a good Data Descriptor?
11
Decades
old
dataset
Standalone
dataset
Data that has
been used in
an analysis
article
Large
consortium
dataset
Data from a
single
experiment
Data that YOU
find valuable
and that others
might find useful
too
Data
associated
with a high
impact
analysis article
13. Visit nature.com/sdata
Email scientificdata@nature.com
Tweet @ScientificData
Honorary Academic Editor
Susanna-Assunta Sansone
Managing Editor
Andrew L. Hufton
Data Curation Editor
Varsha K. Khodiyar
Advisory Panel and Editorial
Board including senior researchers,
funders, librarians and curators
Supported by
Editor's Notes
Scientific Data is an open-access, peer-reviewed publication for descriptions of scientifically valuable datasets. Our primary article-type, the Data Descriptor, is designed to make your data more discoverable, interpretable and reusable.
Our article formats differ from standard research articles. Our article sections encourage authors to provide detailed descriptions of their dataset, without emphasis on their interpretation. Data Descriptors also include formal data citations that help the community track dataset reuse and maintain tight linking between the article and the external data records.
Machine-readable metadata files support each publication, and help maximize reuse value for advanced users.