Guidelines on research data management at the FSU Jena

Guidelines and Principles

Guidelines on research data management at the FSU Jena
Image: Roman Gerlach

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.

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 (URZ, ThULB, SFT, Legal Office), the scientific community, the vice-president for research, and the research data management helpdesk.

The policy on the handling of research data [pdf 170KB] provides a first overview on general recommendations and best practices while working with research data. The guidelines and recommendations [pdf 316KB] complement the policy and specify the general recommendations.

Deutsche Forschungsgemeinschaft (DFG)

In July 2019, the DFG published the code "Guidelines for Safeguarding Good Scientific Practice" (German, 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.

European Commission - Horizon 2020

At the end of 2013 the European Commission launched the Pilot to open up publicly funded research data ("Open Research Data Pilot"). 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 on Open Access to Scientific Publications and Research Data in Horizon 2020 (PDF, version 3.1, 25 August 2016).

FAIR Data Principles

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).

Findable Show content

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 Show content

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 Show content

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 Show content

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.

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