Project planning

Requirements of funding organizations for the handling of research data

Many third-party funders expect information on the handling of research data as part of a funding application for the allocation of funds from certain funding lines. The requirements of the funding bodies are heterogeneous and sometimes differ depending on the funding programme. More and more frequently, accessibility to the research data created in the project is expected after project completion. Some funders also require a data management plan (DMP) as part of the funding application or during the first six months of the project.

Please note that the requirements may differ in different calls for proposals or funding programmes of the same funding body. The respective current requirements should be checked individually.

German Research Foundation (DFG)

  • Information on the handling of research data is mandatory in project proposals. The DFG provides a checklist for this purpose.
  • Research data should be published as soon as possible in a relevant, supraregional infrastructure, provided that no third-party rights conflict with this.
  • Research data should be stored for at least 10 years in accordance with good research practice.
  • Further requirements: "Data should be made accessible at a stage of processing that allows it to be usefully reused by third parties (raw data or structured data). To make sure this is the case, it must be ensured that access to the data is still guaranteed when, through publication, the rights of use relating to research data are transferred to a third party, usually a publishing house."
  • Cost absorption is possible for project-specific costs incurred for the re-use of the research data.

Further information:

Handling of research data. Checklist for planning of handling of research data in research projects (21th December 2021).

DFG Guidelines on the Handling of Research Data (2015).

Proposal Preparation Instructions - Project Proposals (09/2022).

Subject-specific Recommendations on the Handling of Research Data

Federal Ministry of Education and Research (BMBF)

  • The requirements for handling research data differ depending on the call for proposals.
  • In general, the BMBF expects a so-called exploitation plan or information on the exploitation of the results as part of the application.
  • In most cases, only the publication of the research results is required. This should be done in a repository. Specific requirements of the funding line must be observed.
  • As a rule, publication should take place after completion of the project.
  • Further requirements are possible depending on the call for proposals.
  • Cost absorption for RDM depends on the respective call for proposals.

Further information:

Current announcements of funding programmes of the BMBF

Volkswagen Foundation

  • Applicants are encouraged to submit a data management plan.
  • Research data should be processed according to FAIR principles if its storage is useful for future research.
  • Research data should be made available as openly as possible.
  • Publication should take place in a public, non-commercial repository with the assignment of a PID.
  • Additional funds are made available for the preparation of research data.

Open Science Policy

Funding Portfolio

Instructions and tips for the application process

European Commission (Horizon Europe 2021–2027)

  • Horizon Europe is the ninth research framework programme of the European Union. It is designed for seven years and replaces Horizon 2020.
  • A data management plan is mandatory.
  • Research data needed to validate results from text publications must be published as promptly as possible. Likewise, all research data specified for publication in the DMP.
  • Publication should be in a trusted repository. A PID is required, metadata must be published under CC0 (or equivalent) licence and data under CC-BY or CC0 (or equivalent) licence. Provision on the project or publisher’s website is not sufficient.
  • Publication should take place as soon as possible. At the latest with the publication of the associated text publication.
  • Open Science measures are defined as mandatory in the Grant Agreement.
  • Further requirements: All research data must be held in accordance with FAIR principles. Exceptions to data publication are possible for specific reasons. Costs for the FDM can be credited. Individual calls may have additional requirements.

Further information:

Funding & tender opportunities

Horizon Europe Grant Agreement

Fact Sheet Open Science

Data Management Plan (DMP)

Even before the project begins, it makes sense to plan in advance how to deal with the research data and results for the coming project phase. A suitable tool for this is a data management plan, which should help the project participants to deal adequately with research data and prepare them for re-use.

Many third-party funders (e.g. the DFG, Horizon Europe or the Volkswagen Foundation) expect information on the handling of research data as part of a funding application for the allocation of funds from certain funding lines.

A DMP should contain information on the following aspects:

  • Origin or collection of data
  • Data documentation
  • Access to the data
  • Responsibilities in the FDM
  • Data archiving
  • Modalities of data publication

Rechtliche Rahmenbedingungen

Please note that the RDM Service cannot provide legal advice. If in doubt, contact the legal office or the data protection office.

Legal questions arise time and again in research data management, such as who "owns" the data collected in the project in the first place, what needs to be considered when publishing it or how to deal with data that contain sensitive information. It makes sense to deal with these and other legal questions at the beginning of a research project. At the latest when publishing your research data after the end of the project, existing rights and obligations must be clarified.

Copyright and Related Rights

Whether or not research data is subject to copyright protection must be examined on a case-by-case basis. The prerequisite for copyright protection is the achievement of a threshold of originality (§ 2 Abs. 2 UrhG). In particular, this must be expressed in a degree of creative freedom that goes beyond normal scientific practice[1]. The attainment of the threshold of originality is not necessarily given, for example, in the case of raw data from measuring instruments. However, by classifying, evaluating or arranging the research data, a sufficient degree of original creation may already result under certain circumstances. Copyright therefore tends to apply more to qualitative than to quantitative data.

In addition to copyright, research data may also be protected by related rights in individual cases. Related rights are property rights that are based on copyright. The achievement of the threshold of originality is not necessary in this case. The related rights apply, for example, to photographs or to the benefit of database producers.

If copyrights or related rights exist, the research data can only be used, passed on and processed with the permission of the respective rights holder. Frequently, several people have rights to a research dataset (co-authorship), so that the consent of all rights holders must be obtained before publication. Furthermore, research data may contain copyrighted material of third parties.


[1] Lauber-Rönsberg, Anne (2021): Rechtliche Aspekte des Forschungsdatenmanagements. In: Praxishandbuch Forschungsdatenmanagement. Hrsg. v. Markus Putnings, Heike Neuroth und Janna Neumann. Berlin: De Gruyter. https://doi.org/10.1515/9783110657807-005, S.90.

Licences

Different licensing models are suitable for the publication of research data, which regulate the conditions under which third parties may reuse research data. Free licences have become established for research data.

One example is the Creative Commons licences, whose "licence modules" allow researchers to link the further use of the research data made available to certain conditions. CC licences only allow use in copyright terms

Licensing under CC0 entails maximum release of the data, which facilitates their subsequent use. However, naming the person(s) who created the work cannot be enforced in this way. Licensing under CC-BY 4.0, which requires attribution and thus simultaneously satisfies the requirement to cite the source from the rules for safeguarding good scientific practice, is more suitable. Licensing under CC-BY 4.0 or equivalent licences is recommended.

Data protection

Research projects often generate data containing personal information. This information, which relates to an identified or identifiable living person (Art. 4(1) DSGVO), may only be collected and processed with the informed consent of the data subjects. Therefore, you should consider at an early stage how you want to handle the research data in the course of the project and after the end of the project and obtain any necessary consents at an early stage. If publication of the research data is planned, corresponding personal or person-related information must be removed (anonymisation). If you have any questions about data protection, you can contact the University's Data Protection Office.

Further information on the topic of law and research data

Baumann, Paul/Krahn, Philipp/Lauber-Rönsberg, Anne (2019): Entscheidungsbaum für die Veröffentlichung von Forschungsdaten. Stand 05/2019. https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-731105.

Forschungsdaten.info: Datenschutzrecht. Schutz von personenbezogenen Forschungsdaten. https://forschungsdaten.info/themen/rechte-und-pflichten/datenschutzrecht/#c279504.

Forschungsdaten.info: Recht und Forschungsdaten. Ein Überblick. https://forschungsdaten.info/themen/rechte-und-pflichten/recht-und-forschungsdaten-ein-ueberblick/.

Kreutzer, Till/Lahmann, Henning (2021): Rechtsfragen bei Open Science. Ein Leitfaden. Hamburg: Hamburg University Press. https://doi.org/10.15460/HUP.211.

Lauber-Rönsberg, Anne (2021): Rechtliche Aspekte des Forschungsdatenmanagements. In: Praxishandbuch Forschungsdatenmanagement. Hrsg. v. Markus Putnings, Heike Neuroth und Janna Neumann. Berlin: De Gruyter. https://doi.org/10.1515/9783110657807-005.

Meyermann, Alexia/Porzelt, Maike: Hinweise zur Anonymisierung von qualitativen Daten. 2014 (forschungsdaten bildung informiert Nr. 1). https://doi.org/10.25656/01:21968.