A presentation given by Marie Timmermann at the 5th LEARN workshop in Barcelona (26 Jan 2017). www.learn-rdm.eu

1. Developing a framework for
Research Data Management Protocols
LEARN Workshop
Barcelona, 26 January 2017
Marie Timmermann
EU Legislation and Regulatory Affairs
Officer
Science Europe

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Science Europe (SE)
Science-Policy Organisation representing the collective interests of
pan-European Research funding bodies as well as European
academic research
Membership: Research Funding and Research Performing
Organisations
43 Member Organisations, 27 countries
Working Groups: aim to make recommendations for the implementation
of policies laid out in the SE Roadmap and other relevant policy areas;
made up of expert level staff from SE member organisations
Bottom-up internal advice by Scientific Advisory Committee (SAC):
30 high-level researchers from 16 countries representing a variety of career
stages and demonstrating a wide spread of research disciplines (including new
and emerging fields)

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Why this topic?
Topic gains importance in the political context of the
Open Science Agenda
SE believes in the development of Open Science in a
way that recognizes the driving role of the scientific
communities in shaping and adopting Open Science
Practices, such as data sharing and reuse.
Discussions around the topic of Open Science usually
focus on topics such as infrastructures and governance;
however, there still is no solution for data management,
which is needed for successful infrastructures and
governance

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Why Science Europe?
SE can be part of the solution because:
SE is well positioned to develop an approach that is
accepted by Performers and Funders
Open Science-relevant
Obvious need
Promote SE values of scientific freedom and
researcher empowerment in the context of a top-down
requirement

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WG Research Data Management Protocols
WG was created with the mandate to continue SE
engagement with Research Data activities with a special
focus on Open Science
Mission: develop and advocate the concept of
‘disciplinary research data management protocols’
(RDMPs) as pragmatic solution to ensure proper
implementation of the Data Management Plans (DMPs).
Representation of both Funders AND Performers in WG
increases credibility and acceptability of WG results

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Objective
The core idea is to formulate ‘protocols’ for the collection
and management of data within specified disciplinary
domains or research communities.
Such ‘protocols’, called Domain Data Protocols (DDPs), are
defined as generally agreed-upon guidelines, or predefined,
written procedural methods.
Instead of having to write, review, evaluate and monitor
individual DMPs, funders and research organisations would
just require project proposers to comply with the DDP
available for the relevant scientific domain.

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RFO/RPO Research Data Management Policies
Data Management Plans (DMPs) are becoming the main
tool to enforce policies on research data management
directed at researchers
Provision of details on data management by
researchers
Aim: monitor and foster data disclosure and sharing
RFOs increasingly require DMPs
H2020 introduces Open Data policy, mandatory DMPs
RFOs and EC creating or reviewing DMP templates

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Outline of the framework
The DMP framework, developed and agreed
upon by the Members of Science Europe, will
set a number of minimal requirements for
disciplinary/community data protocols.
These requirements will have close
resemblance to the requirements of current
DMPs and will fit perfectly in data policies that
have been or are being formulated.

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Advantages of the approach
• Prevent situations where scientific domains or scholarly
communities find top-down requirements or templates for
DMPs not applicable or not useful for their field/research
• Better DMP acceptance by researchers and better
researcher engagement in research data management
• Provision to researchers of a learning vehicle on research
data management practices in their field, thus raising the
general quality level of RDM; and
• Reduced DMP processing costs and burdens for
funders, and more focus on and better assessment of
deviating RDM solutions

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DMPs for researchers & RPOs
Modular protocols to be formulated and adopted by
research communities will make life easier for researchers:
Researchers can refer to the data protocol to be
followed instead of inventing out the DMP wheel
individually
Protocols will raise quality standard of DMPs and
will be regarded as useful, in turn DMPs will be a
stronger tool
Counter situation that researchers see RDM as yet
another bureaucratic requirement
Can cover all research outputs relevant for Open
Science

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DMPs for RFOs
Framework for Protocols to be defined by RFOs and RPOs
will make life easier for funders:
Instead of checking thousands of individual DMPs,
endorse disciplinary/domain/community protocols
DMP will not be a paper tiger, impossible to check
whether it is obeyed during execution of research
project

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The WG’s approach I
5 Task forces worked on different aspects
Framework elements: content / volume / data
character (digital and non-digital)
DMP drafting, execution and follow-up
FAIR principles / Costs
Responsibility for the data / Acknowledgement
(including unique identification) and crediting
RDM workflows / Prioritisation of data to be kept:
criteria for the eligibility of data for keeping, access
management, timing for disclosure
Proof of concept partnerships

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The WG’s approach II
The Task Forces’ work will be merged into a report on
the framework
The framework is compared against existing models and
frameworks
The framework has been submitted to various
communities for feedback and proof of concept
Final report will be ready in March and the concept will
be presented at the RDA conference in Barcelona
beginning of April

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Comparison: LERU Roadmap
Broader approach of the Roadmap, but core ideas seem
similar:
Support re-use of data
Foster individual solutions for individual entities
(universities, disciplines) according to their needs
“development and adoption of an institutional data policy
with accompanying guidance”
“researcher’s responsibility … that good data management
practices are implemented from the outset of a research
project, e.g. through the creation of a data management
plan that is in line with the requirements of the policies of
the research funder.”

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Further Information
www.scienceeurope.org
Rue de la Science 14
1040 Brussels
marie.timmermann@scienceeurope.org