3:AM in BUCHAREST| September 28-29, 2016
Evaluating the possibilities of DataCite for
developing ‘Open data metrics’ on the
production and usage of datasets worldwide
Nicolas Robinson-Garcia, Phillipe Mongeon, Wei Jeng & Rodrigo Costas
Promotion of data sharing infrastructures
• Data repositories
• Data Citation Index
• Persistent linkages (DOIs)
Promotion of data sharing practices
• Data sharing incentives
• Perceived benefits
Sharing and citing data
DATA CITATIONS
Promotion of data sharing infrastructures
• Data repositories
• Data Citation Index
• Persistent linkages (DOIs)
Promotion of data sharing practices
• Data sharing incentives
• Perceived benefits
Sharing and citing data
DATA CITATIONS
Maximizing investment
Searching for evidences
of data sharing
Aims of this study
1.Who shares data?• Which countries are sharing scientific data
(in DataCite)?• Are there biases by discipline (in DataCite)?
2.Are there evidences of data reuse?• Are researchers using DOIs to link papers to
datasets?• Are they mentioning datasets through social
media?
Citations to publications• Based on researchers’ communication patterns
• Influenced by research evaluation schemes
• Highly standardized and extended within the scientific practice
Citations to datasets• Promoted by funding bodies
• Not embedded on scholarly communication patterns
• Heterogeneous forms of acknowledgement (paper, dataset, none…)
From citing papers to
citing data
The metadata schema of
DataCite
Mandatory fields
Source: DataCite Metadata Working Group (2016).
http://doi.org/10.5438/0012
Citations to data
Recommended format
Source: DataCite Metadata Working Group (2016).
http://doi.org/10.5438/0012
Creator (PublicationYear):
Title. Publisher. Identifier
Preliminary results
Types of data
Preliminary results
Availability of Publisher information
Preliminary results
What is a Publisher?
Preliminary results
Citations Altmetric.com
(Twitter)
DataCite records with DOI 6352875
Records with metrics (matched on DOI) 6432 14314
%records with metrics 0.10% 0.23%
Intensity (records with metrics/metric) 17.9 4.1
• Citation and altmetric analysis
• Matches based only on DOIs!
The no. 1s
The most cited dataset?
The most tweeted dataset?
Preliminary results
Country of origin based on publisher infoCountry # Records
UK 1728428Germany 966289
Switzerland 591062USA 560799
Canada 81471Spain 32795
Netherlands 26791Italy 25241
Australia 21059Ireland 19416Austria 18571
USA, UK 12981France 9443
Denmark 8804BE,DE,IT,NL,ES 5366
Sweden 2816Korea 2
Preliminary results
Country of origin based on publisher info
Bibliometric limitations
Technical
Heterogeneity of sources
Lack of basic data (affiliation)
Lack of standard normalisation
Conceptual
Publication vs. Data production patterns
Data citations vs. Data reuse
Conceptual heterogeneity
Some examples
Publication author vs. Data producer distribution
Authors (non disambiguated) WoS records Creators DataCite records
WANG, Y 56596 Geml, József 487363
ZHANG, Y 54203 Ryberg, Martin 487351
WANG, J 49817 Lumbsch, H.
Thorsten487350
LIU, Y 46307 Tedersoo, Leho 487350
LI, Y 45773 Hampe, Felix 487350
Most productive data
creator
Some examples
[ "
#IHaveWrittenMyOwnOneNewScientificPaperOnTheGeographyAndMarsLif
e. #IHaveAlreadySuccessfullyOFFICIALLYPublishedItOn #DiscoveryNews
#ScienceAlert #DiscoveryChannelIndia #AndAlsoOn
#DiscoveryCommunications
#AndItsOFFICIALPublicationIsThereOnAllOfItSoPlea
Heterogeneity of Publisher information
Phys.Rev. C75 (2007) 045203
ETH-Bibliothek Zürich, Bildarchiv / Fotograf: Unbekannt / Fel_027418-
VE / Public Domain Mark
(see the metadata of copyright: http://www.e-
pics.ethz.ch/index/ethbib.bildarchiv/ETHBIB.Bildarchiv_Fel_008192-
RE_257002.html)
JHEP 1311 (2013) 183
References
DOI numbers
Copyright
statements
Hashtags???
3:AM in BUCHAREST| September 28-29, 2016
Thank you!
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