Over the past years, funding agencies and other initiatives released a number of principles and guidelines 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.
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 (URZ de, ThULB, 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 data [pdf, 170 kb] de provides a first overview on general recommendations and best practices while working with research data. The guidelines and recommendations [pdf, 316 kb] de complement the policy and specify the general recommendations.
In July 2019, the DFG published the Code of Conduct "Guidelines for Safeguarding Good Research Practice" (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 Data provides a comprehensive compilation of principles, support and funding. For some disciplines, also subject-specific recommendations can be found on this website.
At the end of 2013 the European Commission launched the Pilot to open up publicly funded research data ("Open Research Data Pilot"). This pilot was extended in 2017 covering all thematic areas now (see Open Reseach Data in H2020). 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 2020 (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 2020 (PDF, version 3.2., 21 March 2017).
The so-called "FAIR Data Principles" which have been published in 2016 have reached a high level of acceptance and general approval. Besides the main points presented in the abridged version below further information on this topic can be found on the web sites of FORCE11 as well as in the article "The FAIR Guiding Principles for scientific data management and stewardship" by Wilkinson, M.D. et al. (2016).
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.
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.
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.
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.