Over the past years, funding agencies and other initiatives released a number of principles and guidelinesExternal link on how to manage research data. When conducting research projects, funding agencies increasingly expect compliance with these guidelines and principles. While planning your research project and writing your proposal we recommend to study the relevant guidelines and clearly state how research data management will be implemented in your project.
Friedrich Schiller University Jena
On December 20, 2016, the senate of Friedrich Schiller University Jena agreed upon a policy on the handling of research data as well as on guidelines and recommendations for research data management. Both documents were developed by a working group on research data management which consists of representatives of the university's central service facilities (UCC, ThULBExternal link, SFT, Legal Office de), the scientific community, the vice-president for research, and the research data management helpdesk.
The policy on the handling of research datapdf, 170 kb · de provides a first overview on general recommendations and best practices while working with research data. The guidelines and recommendationspdf, 316 kb · de complement the policy and specify the general recommendations.
Since July 2023, the university's statutes for Safeguarding Good Research Practice de have also included statements on research data and software that comply with the DFG Code of Conduct mentioned below.
Deutsche Forschungsgemeinschaft (DFG)
In July 2019, the DFG published the Code of Conduct "Guidelines for Safeguarding Good Research Practice"External link (coming into effect 01.08.2019). It replaces the memorandum on Safeguarding Good Scientific Practice (1998, 2013, with English part) which had been in effect until then. Already in September 2015, the DFG senate adopted new Guidelines on the Handling of Research Data. The DFG website Handling of Research DataExternal link provides a comprehensive compilation of principles, support and funding. For some disciplines, also subject-specific recommendations can be found on this website.
On March 14, 2022, the German Research Foundation specified the requirementsExternal link for handling research data in funding proposals. Specific information on the handling of research data, based on a catalog of questionsExternal link, (as of December 2021) is now made mandatory by the DFG.
Research Software
Given the increasingly widespread use of Research Software, the handling of this tool becomes more and more important. For transparent and comprehensible research, it is more important than ever to make the used research software easily visible and accessible. Some principles and guidelines already exist and can be found here:
- „Grundlagen und Prinzipien der Förderung“External link
- Handreichung zum Umgang mit ForschungssoftwareExternal link
- Umgang mit Forschungssoftware im Förderhandeln der DFG.External link
European Commission - Horizon 2020
Horizon 2020
At the end of 2013 the European Commission launched the Pilot to open up publicly funded research dataExternal link ("Open Research Data Pilot"). This pilot was extended in 2017 covering all thematic areas now (see Open Reseach Data in H2020External link). Open data has become the default, although grantees may opt out under certain conditions. The two most important guidelines are the Guidelines on FAIR Data Management in Horizon 2020External link (PDF, version 3.0, 26 July 2016) and the Guidelines to the Rules on Open Access to Scientific Publications and Open Access to Research Data in Horizon 2020External link (PDF, version 3.2., 21 March 2017).
Horizon Europe
The new EU framework program Horizon Europe requires immediate open access to publications that have undergone a peer-review process. Embargo periods of six or twelve months, after which a publication had to be freely accessible, as was still the case in the Horizon 2020 program, are no longer envisaged.
In Horizon Europe, free access to research data is also to be guaranteed in principle, in accordance with the principle "as open as possible - as restricted as necessary". In dealing with research data, researchers are to be guided by the FAIR principles. This includes, the mandatory creation of a data management plan in each project and the storage and provision of data in a relevant repository. All other guidelines are described in the Horizon Europe Program GuideExternal link.
The creation of a Data Management Plan (DMP) for ERC projectsExternal link is mandatory from 2021 onwards. The DMP must be provided at the latest 6 months after the start of the project.
FAIR Data Principles
The so-called "FAIR Data PrinciplesExternal link" which have been published in 2016 have reached a high level of acceptance and general approval. Further information on this topic can be found in the article "The FAIR Guiding Principles for scientific data management and stewardship" by Wilkinson, M.D. et al. (2016)External link.
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Findable
F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. metadata clearly and explicitly include the identifier of the data it describes.
F4. (meta)data are registered or indexed in a searchable resource. -
Accessible
A1 (meta)data are retrievable by their identifier using a standardized communications protocol.
A1.1 the protocol is open, free, and universally implementable.
A1.2 the protocol allows for an authentication and authorization procedure, where necessary.
A2 metadata are accessible, even when the data are no longer available. -
Interoperable
I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (meta)data use vocabularies that follow FAIR principles.
I3. (meta)data include qualified references to other (meta)data. -
Re-usable
R1. (meta)data are richly described with a plurality of accurate and relevant attributes.
R1.1. (meta)data are released with a clear and accessible data usage license.
R1.2. (meta)data are associated with detailed provenance.
R1.3. (meta)data meet domain-relevant community standards.