Guideline for the funding of projects to strengthen the data skills of young scientists

1 Funding objective, purpose of funding, legal basis

1.1 Funding objective and purpose

The continuous development of new digital research methods and the increasing amount of available research data enable the application of such methods in more and more research fields. In this context, new research questions can be developed and existing research questions can be addressed for the first time or in a new way with the help of different data-driven analyses. However, the necessary digital and data-related skills are often not available where they would make this possible. Accordingly, there is great potential to anchor data-driven work more broadly and deeply in various scientific fields, which can be exploited by strengthening (subject-specific) data expertise. This can also contribute to cultural change in these subjects. This is in line with the goals formulated in the German government's data strategy to significantly increase data literacy in science, among others, and to establish a data culture as well as to promote responsible data use and leverage innovation potential. Increasing data literacy and promoting data-based innovations are also central components of the Federal Ministry of Education and Research's (BMBF) Research Data Action Plan, which is anchored in the German government's data strategy. Building data literacy in science is also essential for working on and with the data infrastructures emerging at national and European level (National Research Data Infrastructure [NFDI] and European Open Science Cloud [EOSC]).

Numerous recently launched measures to teach data competencies at universities start at the undergraduate level. In contrast, not enough attention is paid to young scientists. However, promoting the teaching of data competencies to young scientists is worthwhile in many respects: among young scientists there is not only a great openness to new methods and possibilities of data-driven research, but also a lot of exchange via conferences and networks. Last but not least, young scientists provide a significant amount of teaching. Increasing the data competencies of young scientists can therefore not only provide better answers to current research questions, but at the same time carry these competencies into the broader community and pass them on.

Accordingly, this funding announcement aims to broaden and deepen the data literacy of young scientists at universities and non-university research institutions in the diverse subjects of the scientific landscape by linking specialized data science skills with subject-specific knowledge. Priority is given to subjects in which data skills are not yet available (to the same extent).

By combining subject-specific research questions with specialized data science methods, the funding implements the above-mentioned goals in a concrete measure. To this end, research projects are funded that are suitable for increasing data competencies in subjects in which these competencies or certain data science methods are not yet established or only established to a selective extent, but in which new scientific findings can be expected.

The added value of projects in which data methods are used innovatively is only really great when new findings from individual projects are carried into the respective subject community and also used there. The present funding guideline therefore aims to support research projects by young scientists in which data competencies are built up, which are then sustainably anchored in the respective subject. In particular, through cooperation and exchange between actors with a subject-related focus on the one hand and a data-related focus on the other, long-term cooperation structures are to be established and a sustainable implementation of data science analyses in different subject-related contexts in the respective subjects is to be advanced.

In this way, Germany should be further strengthened internationally as a center of science, and the international connectivity of data-based science should be ensured. At the same time, it is to be expected that an increase in the data competencies of young scientists across research disciplines can also increase the innovation potential in industry if some of the young scientists contribute the corresponding competencies to cooperation projects with companies or if young scientists move to industry.

1.2 Legal basis

On the basis of the present open-topic announcement, the BMBF will fund research projects involving scientists who are at the doctoral or postdoctoral stage or who head a junior research group. The funding is intended to answer research questions with the help of data analyses that have not yet been established in the relevant specialist culture. For this purpose, collaborations should be entered into with partners within or outside the applicant institution who can demonstrate distinctive competencies in data science methods. The project description must show that this exchange would not have taken place without the funding. In addition, it must be convincingly demonstrated how the newly acquired data competencies will be used beyond the funded project to ensure anchoring of the methodology that is new to the discipline.

Innovative use of existing data is to be funded, but not the collection of new data sets or the construction of databases. The application must describe the data with the help of which the analyses will take place.

This does not mean that the data must already be in a form where analysis can begin immediately; however, the focus of the project should be on data analysis and data preparation should be minimal.

Funding is provided for projects on research questions that can be answered innovatively with the help of data analysis. To this end, cooperation between data-related and subject-related actors is to be established in order to expand and deepen the data competencies of young scientists on the basis of concrete research projects. To this end, collaborations are to be newly established in order to apply previously unused data analyses or data science methods in a new subject-related context. The partners of the collaboration must be known at the time of application, but should not yet be collaborating for the purpose of applying data science methods in the respective subject area. It must be clear from the project application that data processing and analysis will not be carried out in the sense of a service by the participant(s) with already existing data competencies. Rather, these tasks are to be performed jointly by both partners in close exchange. In this way, data competencies are to be built up on the one hand and a deeper understanding of possible use cases is to be created on the other.

2. Object of the financing

2.1 Funding requirements in detail

Funding is provided for projects whose scientific relevance and data-methodological suitability for the research question give rise to expectations of impulses for research in the respective subject. Ideally, this means that a method that can also be applied to other topics is used to address a question that has so far only been answered to an insufficient extent. The methods used do not necessarily have to be developed from scratch, but they must not yet be established in the relevant community.

2.1.1 The added value generated by the planned project for the specialist community must be presented in a coherent and comprehensible manner. In particular, it must be shown how research questions can be addressed that have not yet been answered or have been answered only inadequately.

2.1.2 In addition, the innovative character of the project must be presented. It must be shown to what extent the methodology planned in the project opens up new possibilities on the technical side, and to what extent it reveals a new field of application from a data science perspective.

2.1.3 The previous qualifications of the applicants must be presented. It must be shown that on the one hand, they already have technical and on the other hand, data science competencies.

2.1.4 Applicants must describe which measures are planned to permanently establish the networking initiated in the project.

3. Recipients of funding

Universities and research institutions are eligible to apply. The existence of an institution serving the non-economic activity of the grantee (university, research institution) in Germany is required at the time of payment of a grant awarded.

Research institutions that receive basic funding from the Federal Government and/or the Länder can, in addition to their institutional funding, only be granted project funding for their additional project-related expenses or costs under certain conditions.

For the conditions as to when state aid is/is not present and to what extent aid-free funding can be granted, see the R&D&I Union Framework.

Both individual and collaborative projects can be funded under this funding guideline.

4. Special funding requirements

5 Type and scope, amount of funding

5.1 Type and amount of funding and funding rate

In the case of non-economic research projects at universities and university hospitals, a flat-rate project allowance of 20% will be granted in addition to the eligible expenses financed by the BMBF.

5.2 Project duration

The duration of the projects shall not exceed 36 months.

5.3 Eligible expenses and costs

Grants may be used primarily for personnel funds, with lower priority for material and travel funds. Eligible for funding are, in particular, measures that are suitable for building up the competence of young scientists through the establishment of collaborations. This primarily includes measures for data analysis, but data preparation and, in exceptional cases, supplementary data collection (on a smaller scale) may also be funded. The procurement or development of software is also eligible for funding in exceptional cases.

The communication of the innovative use of methods within the research community and to the interested public, for example through conference contributions or the organization of a project-specific event, is explicitly desired. Corresponding measures are also eligible for funding.

Technical infrastructures are not eligible for funding.

6 Other funding regulations

7 Procedure

7.1 Involvement of a project management organization, application documents, other documents and use of the electronic application system

7.2 Single-stage application procedure

Applications received after the date specified above may not be considered.

7.2.2 Application documents

The grant application must be specifically related to the criteria in this policy and must include all material statements used to evaluate and assess the appropriateness of the grant. Grant applications that do not meet the listed requirements will not be considered.

It is recommended that contact be made with the PT at the time the grant application is prepared.

In the case of collaborative projects, funding applications must be submitted in consultation with the intended collaborative coordinator. The project descriptions are to be submitted only by the intended collaborative coordinator as a collaborative project description in agreement with all parties involved.

Each application for a collaborative project must be accompanied by a cover letter/preliminary sheet for submission on which a representative (usually the project manager) confirms by signature that he/she has read and understood the information provided in the collaborative project description and that it is correct.

The detailed description of the project should include the following sections:

1. formulation of a concrete research question that is to be addressed with the help of data science methods and that can only be answered through the use of this methodology.
2. international state of the art, especially concerning the use of data science methods in the respective subject and in the respective thematic environment of the chosen research question.
3. existing competences and experiences in relation to the research project of both partners (subject-related and data-related)

Relevant subject-related expertise of the subject-related partner Data competencies and experience with data science methods of the subject-related partner relevant data competences of the data-related partner Experience and previous knowledge of the data-related partner in working with subject-related cooperation partners.

4. description of the available data to be used in the project.
5. outline of a rough research designs

Methodological approaches Idea of what results will be achieved and what new knowledge will be gained.

6. detailed description of the work program with special emphasis on the collaboration between the partners involved, including milestone, time and resource planning per work package (for collaborative projects in overview for the collaborative and in detail for the applicant).
7. networking and cooperation concept for the collaboration of the involved parties.
8. contribution of the research project to the further development of the respective subject through the sustainable anchoring of the newly acquired competencies in the project.
9. contribution to the competence development of young scientists.
10. exploitation plan, in particular dissemination and anchoring of the results in the two participating specialist communities.
11. necessity of the grant and presentation of the result of the examination of alternative funding possibilities.

To be included in the appendix:

Curricula vitae of already known project personnel including the intended project leadership of the applicant institution(s),
If required, "Letters of Intent" from additional participants.

Deviation from the format and content requirements may result in devaluation of the grant applications or, in the case of significant deviations, exclusion from the competition. 7.2.3 Evaluation criteria

7.3 Regulations to be observed

Berlin, August 17, 2021, Federal Ministry of Education and Research . On behalf of A. Herdegen.