There are several ways to get a research project funded if you are a researcher in Germany. This includes public sector funding, industry funding and funding by foundations. An overview over these different types of available funding can be fund on the pages of the Federal Ministry of education and Research (BMBF). The BMBF itself is also one of the biggest research funders in Germany.
The biggest public-sector research funder in Germany, however, is the Deutsche Forschungsgemeinschaft (DFG). The self-governed foundation is financed by the federal and state governments and has a yearly funding budget of approximately three billion Euros. More information on their funding programms can be found on their English pages.
Of course, you can also apply for funding from supranational institutions such as the European Commission and their current frame work programme Horizon 2020 or from internationally operating trusts such as the Wellcome Trust .
Most funders have introduced research data management guidelines in recent years. German funders often follow the lead of the European Commission and their research data management guidelines and requiremenmts. The general expectation has come to be that research data are a public good, often originating from publically funded research projects, and should as such be made available openly or with as few limitations as necessary wherever possible.
Many funders such as the Wellcome Trust and the European Commission require in their guidelines that applicants submit a „data management plan“ (DMP) or a „data sharing plan“ along with their application which describes how research data will be managed and shared during and after the research project. The „Guidelines on Data Management in Horizon 2020“ also specify that data have to be managed according to the F.A.I.R. principles which measns that they have to be handled in such a way that ensures they will be findable, accessible, interoperable and re-usable during and after the research project .
German funding organisations such as DFG and BMBF have also made it mandatory to provide information on the re-use of the research data after the end of the project and usually require for the data to be made accessible in a (data) repository. Costs associated with data management can also be reimbursed if included in the original application, but not after the fact.  This is another reason to think about data management early on and create a DMP.
The following tables provide an overview on what, specifically, the different funding organisations require.
|Funder||BMBF||DFG||EU Horizon 2020||Wellcome Trust|
|What to archive? ||research data||research data|
reserach data, unpublished data, programming code
Where to archive?
|data archive/repository||free choice of repository||free choice of repository||no specific stipulation, but must be archived|
|When to archive?||after project end||within 12 months after project ends||as soon as possible||immediately after publication|
General terms and conditions
|data need to be longterm-archived/ preserved for the scientific community|
primary data have to be stored for 10 years in their institution of origin
|a data management plan and making data openly available after the project ends is mandatory for all projects with start date after 01/2017||mandatory for all projects whose data can be shared and re-used; re-users have to cite the data source and keep to the re-use license conditions|
|What to archive? |
research data, unpublished data, programming code
|research data, accompanying information||research data|
|Where to archive?||free choice of repository, GenBank and PDB suggested||free choice of repository, HEPDATA and INSPIRE suggested||free choice of repository, zenodo (OpenAIRE all-purpose repository) suggested|
|When to archive?||within 6 months after the project ends|
as soon as possible
|General terms and conditions||Archiving (nucleotid- / proteine sequences, makromolecular atom coordinates, anonymised epidemiological data) to be done upon publishing of results||different access stipulations for different projects: use of CC licences and DOIs is recommended||mandatory for all new projects from 2010 and all projects financed by the EUR consortiums|
The bidding process
The world of funding bids and grant applications is one of fierce competition. Usually a bid involves going through a complex, time-consuming evaluation and selection process and several groups of reviewers and decision makers.
A DFG bid, for example, takes at least 6-9 months whereas BMBF bids can take as long as 15 months to be completed. Application evaluations for Horizon 2020 bids can take up to ten months plus a contract preparation period of several weeks.
DFG exclusively funds fundamental research projects. Other funding institutions such as ministeries and foundations mainly support application-oriented research.
What to consider while writing a funding/grant application
Every research proposal has to contain a statement on what kind of knowledge it expects to gain on a clearly defined scientific topic or a socially relevant issue. The most important part of every proposal is the proposal text itself which usually consists of four main segments:
- Basic information about the applicant
- Research exposé containing the state of research (one's own as well as generally), research goals, hypotheses and methodology overview
- Time schedule and budget, oftentimes a data management plan and/or other information about sharing of research data
Oftentimes, a so-called "expression of interest" (a short overview of the research proposal) is required before submitting an actual bid. If convinced, the funding institution will then issue a formal request for a bid. Smaller funding institutions like some foundations do not usually require these two separate steps.
After funding for a proposal is granted, the project now has to conform to the funding institution's policies. Fund allocation is usually linked to so-called „deliverables“ such as regular project/progress reports and detailed financial reports. Funders such as the DFG also expect a statement on the management of research data or even a data management plan which will help documenting things in order to fulfill one's reporting obligations.
Why you should use a DMP even if your funder doesn't explicitely require one
It makes sense to create and use a data management plan even if it is not required since it will help you think through the following issues:
- What kind of data will be created/collected?
- How much storage space will be needed?
- Who will have access to the data during the project and after the project?
- What publications based on the data are being planned?
By systematically recording the answers to these questions in a DMP, uncertainties and potential issues can be more easily identified and addressed early on.
- ↑ Guidelines on FAIR Data Management in Horizon 2020
- ↑ See Richtlinien zum Umgang mit Forschungsdaten by the DFG and the BMBF Bekanntmachung