2013 DataCite Summer Meeting - Making Research better DataCite. Co-sponsored by CODATA. Thursday, 19 September 2013 at 13:00 - Friday, 20 September 2013 at 12:30 Washington, DC. National Academy of Sciences http://datacite.eventbrite.co.uk/

1. DISCOVERY, ACCESS, AND CITATION
OF PUBLISHED RESEARCH DATA
NIGEL ROBINSON
20 SEPTEMBER 2013
THE DATA CITATION INDEX - PARTNERSHIP WITH DATACITE

2. ©2010ThomsonReuters
OVERVIEW
• What is the Data Citation Index?
• Building the Data Citation Index
• Challenges
• Partnership with DataCite

3. ©2010ThomsonReuters
DEPOSITION OF DATA BY RESEARCHERS
3
24%
36%
47%
51%
17%
Publisher website
Repository managed by a
third party (e.g, domain-…
Department or institutional
repository
Personal website
Other
Q16. Where do you place your non-traditional scholarly output to
make it available to others? (n=471)

4. ©2010ThomsonReuters
RESEARCHERS NOT RECEIVING CREDIT
4
Barriers to creating and
sharing data:
• Researchers are hesitant to spend
time and effort to create and share
data because they don’t feel the
work is adequately exposed or
accredited
•Researchers find are finding it
difficult to expose data they have
produced because data repositories
do not have clear standards or
mechanisms in place for doing so

5. ©2010ThomsonReuters
BARRIERS TO RESEARCHERS CITING
DATA
Researchers agree that data should be cited, but there are
currently no universally accepted standards for citing data
5
“Lack of knowledge about standards for citation and of proper
scholarly recognition and/or evaluation of such materials.”…
“…cumbersome citation formats including very long internet
addresses.”
“Incomplete citation information available (dates and real
author names as distinct from aliases)’”

6. ©2010ThomsonReuters
BENEFITS OF RESEARCH DATA SHARING
• Advancement of
scholarship
• Verification of
results
• Promotion of
scholar’s work

7. ©2010ThomsonReuters
RESEARCHER PROBLEMS
• Access & discovery
• Citation standards
• Lack of willingness to deposit and cite
• Lack of recognition / credit

8. ©2010ThomsonReuters
IMPACT ON RESEARCH LIBRARIES
8

9. ©2010ThomsonReuters
DATA CITATION INDEX AIMS
Launched October 2012
3M data records
• Enable the discovery of data
repositories, data studies and data
sets in the context of traditional
literature
• Link data to research publications
• Help researchers find data sets and
studies and track the full impact of
their research output
• Provide expanded measurement of
researcher and institutional research
output and assessment
• Facilitate more accurate and
comprehensive bibliometric analyses

10. ©2010ThomsonReuters
As we evaluate repositories for
inclusion, some of the things we
consider are:
• Editorial Content - ensuring that
material is desirable to the
research community.
• Persistence and stability of the
repository, with a steady flow of
new information.
• Thoroughness and detail of
descriptive information.
• Links from data to research
literature.
REPOSITORY SELECTION & EVALUATION

11. ©2010ThomsonReuters
REPOSITORY EVALUATION
• Repository must hold data
• Repository must provide access to dataData deposit
• Material added/updated
• Provide statistics on deposited data
• Actively curate data in the archive
Active
• Persistent IDs, DOIs or other permanent ID
• Contacts available for confirmation of interpretation
• Indication of intention to preserve data or provide
access over the long term
• Contingency if repository was to cease to operate
• Make data accessible (or state licensing terms)
• Sustainable
• Funding information available for repository and
deposited data
Persistent
• Links to literature
• Citation in literature databasesProof of reuse

12. ©2010ThomsonReuters
DATA REPOSITORIES
• Over 850 repositories identified

13. ©2010ThomsonReuters
TYPES OF DATA BY DISCIPLINE
ART & HUMANITIES
CULTURAL
HERITAGE
LANGUAGE CORPUS
IMAGE
COLLECTIONS
RECORDINGS
SOCIAL SCIENCES
POLL DATA
ECONOMIC
STATISTICS
LONGITUDINAL DATA
NATIONAL CENSUS
PUBLIC OPINION
SURVEYS
SCIENCE &
TECHNOLOGY
MAPS
ALGORITHMS
GENOMICS
SKY SURVEYS
ASTROPHYSICS
REMOTE SENSING
MUSEUM SPECIMENS

14. ©2010ThomsonReuters
INDEXING A DATA REPOSITORY
ON WEB OF KNOWLEDGE
• Repository/Source: Comprises data
studies, data sets and/or microcitations.
Stores and provides access to the raw
data.
• Data Study: Descriptions of studies or
experiments with associated data which
have been used in the data study.
Includes serial or longitudinal studies
over time.
• Data Set: A single or coherent set of
data or a data file provided by the
repository, as part of a collection, data
study or experiment.
• Microcitation: (nanopublication) An
assertion about concepts that have
been found to be linked by scientific
enquiry, and can be uniquely identified
and attributed to its author. Made up of
three separate parts: a subject, a
predicate and an object.
14
Record Types
Descriptive
metadata
feed from
repository
Repository
raw
metadata is
analysed
Metadata
added
Repository
Data study
Data set
Micro-
citation

15. ©2010ThomsonReuters
Search Results within the
Data Citation Index
present the powerful Web
of Knowledge options for
exploring a body of
information.

16. ©2010ThomsonReuters
Link to all Data Citation Index
content associated with this
particular Repository.

17. ©2010ThomsonReuters
Link out directly to the
original item, in this case
a Data Study.

18. ©2010ThomsonReuters
REQUIREMENTS & CHALLENGES
• Metadata availability
– Lack of repository resources
– Lack of repository expertise
• Citable data source
• Metadata quality
– Clean & consistent metadata
– Metadata inconsistencies
– Consistent file format
• Desirable characteristics
– English language for key metadata fields
– Metadata curation and quality control
– Required metadata fields present for citation
– Data dictionary and schema available
– Consistent metadata to allow mapping to DCI fields
– Member of extended network
• Data repositories are not static
• Partnerships

19. ©2010ThomsonReuters
Data
Citation
Index
Repository
1
Repository
2
Repository
3
DATA CITATION INDEX - METADATA
PARTNERSHIPS
DataCite
Repository
1
Repository
2
Repository
3
Data
Citation
Index
DataCite

20. ©2010ThomsonReuters
DATACITE PARTNERSHIP
• Repositories providing enhanced metadata to
DataCite are included in the Data Citation
Index
– Expanded data visibility through Web of Knowledge
– Faster and more frequent updates
– Encourage use of DataCite DOIs and citation
formats
– Tracking of citations to their data in the primary
research literature
– Demonstrate value of citation

21. ©2010ThomsonReuters

22. ©2010ThomsonReuters
DATA CITATION BEHAVIOUR
Current citation style
(in full text of article)
Desired/future citation style
(as part of cited references)
U.S. Dept. of Justice, Bureau of Justice Statistics
(1996): MURDER CASES IN 33 LARGE URBAN
COUNTIES IN THE UNITED STATES, 1988.
Version 1. Inter-university Consortium for Political
and Social Research.
http://dx.doi.org/10.3886/ICPSR09907.v1
Lee, Seung-Jae; Lee, He-Jin; Cho, Ji-Hoon; Rho,
Sangchul; Hwang, Daehee (2008): GSE11574: The
responses of astrocytes stimulated by extracellular a-
synuclein. Gene Expression Omnibus.
http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=G
SE11574

23. ©2010ThomsonReuters

24. ©2010ThomsonReuters
DATA CITATION INDEX
• Discovery of data most important to scholarly
research
• Data linked to published research literature
• Measures of data citation, use and reuse
• New metrics for digital scholarship

25. ©2010ThomsonReuters
Thank you
Nigel Robinson
nigel.robinson@thomsonreuters.com