Research data management in the French National Research Center (CNRS)

Date03 April 2018
Publication Date03 April 2018
Pages248-265
DOIhttps://doi.org/10.1108/DTA-01-2017-0005
AuthorJoachim Schöpfel,Coline Ferrant,Francis André,Renaud Fabre
SubjectLibrary & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Metadata,Information & knowledge management,Information & communications technology,Internet
Research data management
in the French National Research
Center (CNRS)
Joachim Schöpfel
GERiiCO Laboratory, University of Lille, Villeneuve dAscq, France
Coline Ferrant
Sociological Observatory of Change, Sciences Po, CNRS, Paris, France;
Northwestern University, Evanston, Illinois, USA and
INRA, Paris, France, and
Francis André and Renaud Fabre
National Scientific Research Center, CNRS, DIST, Paris, France
Abstract
Purpose The purpose of this paper is to present empirical evidence on the opinion and behaviour of French
scientists (senior management level) regarding research data management (RDM).
Design/methodology/approach The results are part of a nationwide survey on scientific information
and documentation with 432 directors of French public research laboratories conducted by the French
Research Center CNRS in 2014.
Findings The paper presents empirical results about data production (types), management (human
resources, IT, funding, and standards), data sharing and related needs, and highlights significant disciplinary
differences. Also, it appears that RDM and data sharing is not directly correlated with the commitment to
open access. Regarding the FAIR data principles, the paper reveals that 68 per cent of all laboratory directors
affirm that their data production and management is compliant with at least one of the FAIR principles. But
only 26 per cent are compliant with at least three principles, and less than 7 per cent are compliant with all
four FAIR criteria, with laboratories in nuclear physics, SSH and earth sciences and astronomy being in
advance of other disciplines, especially concerning the findability and the availability of their data output.
The paper concludes with comments about research data service development and recommendations for an
institutional RDM policy.
Originality/value For the first time, a nationwide survey was conducted with the senior research
management level from all scientific disciplines. Surveys on RDM usually assess individual data behaviours,
skills and needs. This survey is different insofar as it addresses institutional and collective data practice.
The respondents did not report on their own data behaviours and attitudes but were asked to provide
information about their laboratory. The response rate was high (W30 per cent), and the results provide good
insight into the real support and uptake of RDM by senior research managers who provide both models
(examples for good practice) and opinion leadership.
Keywords Data preservation, Open Science, Research data management, Data sharing, Data curation,
FAIR principles
Paper type Research paper
Introduction
In the era of Open Science, research data management (RDM) is important though not new
challenge for research performing organizations. Not exactly a delimited concept, RDM is an
umbrella term for activities related to the creation, organization, structuring and naming of
data; to their backup, storage, conservation and sharing, and to all actions that guarantee
data security. It aims to ensure reliable verification of results and permits new and
innovative research built on existing information(Whyte and Tedds, 2011). Research data,
as one part of the scientific output, must be understood in a broad sense, as the recorded
factual material commonly accepted in the scientific community as necessary to validate
research findings[1]. Sometimes, they are just generalized as digital research output
Data Technologies and
Applications
Vol. 52 No. 2, 2018
pp. 248-265
© Emerald PublishingLimited
2514-9288
DOI 10.1108/DTA-01-2017-0005
Received 31 January 2017
Revised 23 December 2017
Accepted 23 January 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2514-9288.htm
248
DTA
52,2
(Pryor et al., 2014, p. VII). But research data are complex objects, dynamic, living, easier to
describe than to define, with characteristics changing along with the research process
(André, 2015). Commonly, the term covers laboratory data (spectrographic, genomic
sequencing, electron microscopy data, etc.), observational data (remote sensing, geospatial,
socio-economic data, etc.), audio-visual data, images, network-based data, plain or
structured text, raw data, statistics, databases, software applications, structured graphics,
etc.; they are inherently collective and come in sets, as a collation of many individual data
(Kowalczyk and Shankar, 2011).
As researchers have shared data with their peers for centuries(Klump, 2017), RDM is
not a new task for large research performing organizations. These organizations are
important data providers, especially because of their large and complex scientific
instruments and projects (Large Hadron Collider, Hubble Space Telescope, Human
Genome Project, magnetic resonance imaging, etc.), and they have a long tradition of best
practices in data management. As a result, their information professionals have developed
more support activities for the RDM than academic librarians (Martin et al., 2017) where
service development is still limited, focussed especially on advisory and consultancy
services rather than on technical services (Cox et al., 2017). What has changed, however, is
the political environment. In the new European strategy towards Open Science[2], RDM
occupies a central place. Open access (OA) to research results, data sharing whenever
possible[3] and data management based on the FAIR principles[4] (Wilkinson et al., 2016)
become the main objectives of scientific policy, which aim at increasing efficiency and
transparency, societal impact and innovation capacity throug h rapid and unrestri cted
dissemination of research results not only by large instruments but also from small-scale
projects and units. The 2017 European Open Science Cloud (EOSC) Declaration endorses
that All researchers in Europe must enjoy access to an open-by-default, efficient and cross-
disciplinary researchdata environmentsupported by FAIR dataprinciples (http://ec.europa.eu/
research/openscience/index.cfm?pg=open-science-cloud). In this new Open Science Policy,
research performing organizations must take action: they have a crucial responsibility for
research data stewardship and should play a major role in supporting an open data culture
(The Royal Society, 2012).
Regarding scientific output (articles, citations) and innovation (patents), France is one
of the leading member states of the European Union. In 2015, French scientists published
nearly 104,000 articles (source: www.scimagojr.com/), and France spent 2.3 per cent of its
gross domestic product on research and innovation (2014) (source: www.oecd.org/).
The French National Center for Scientific Research (CNRS[5]) is the largest fundamental
public research organization in Europe. It carries out research in all fields of knowledge,
through its 10 institutes (life sciences, chemistry, physics, etc., Table I) and 32,500 staff
members in more than 1,000 research units (laboratories), most of them run in parallel
with universities and/or other research organizations. In 2017, France joined the
International Support and Coordination Office set up by Germany and the Netherlands to
support the GO FAIR initiative which aims to gradually open up existing research
data at scientific and academic institutions in all research fields and across national
borders”–and is thus a stepping stone towards the realization of the EOSC
mentioned above (www.government.nl/latest/news/2017/12/01/progress-towards-the-
european-open-science-cloud).
One of the first signatories of the Berlin Declaration on OA, the CNRS is deeply
committed to OA. Also, the CNRS supports national and international initiatives, projects
and infrastructures fostering OA to research results, with a clear preference for
self-archiving of publications and data[6] in open repositories (green road). Recently, the
CNRS has confirmed its attachment to the values of Open Science, considering research
data as common goodsthat should be shared with the scientific community whenever
249
French
National
Research
Center (CNRS)

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