Requirements of funding agencies on data management and data sharing differ across countries and across funding agencies. Some agencies provide elaborated guidance and templates for data management plans (DMPs), while other agencies do not. You can use the data management planning section of the DataWiz assistant in order to generate a DMP that is adjusted to your funding agency’s requirements.
This section of the knowledge base is focused on requirements of German funding agencies. Researchers from UK may be interested in the Data Curation Center’s list of funders’ data management and sharing requirements, while researchers from the US will find information in the list of funders’ data management and sharing requirements by DMPtool.
German Research Foundation (DFG)
For psychological projects funded by the DFG, the following guidelines apply:
- The Recommendations on Safeguarding Good Scientific Practice (see also the knowledge base’s section on data policies).
- The Guidelines on the handling of research data:
- The DFG (2015, p. 1) requires applicants to outline the project’s data sharing plan in proposals and to “consider during the planning stage whether and how much of the research data resulting from a project could be relevant for other research contexts and how this data can be made available to other researchers for reuse. […] Details should also be provided on any third-party rights affected and preliminary planning for the data publication schedule.’ In general, research data has to be shared as soon as possible: ‘Assuming that the publication of research data from a DFG-funded project does not conflict with the rights of third parties [. . .], research data should be made available as soon as possible.” Moreover, scientific communities were called upon to develop discipline-specific guidance.
- Schönbrodt, Gollwitzer and Abele-Brehm (2016) developed the discipline-specific guidance of the German Psychological Association (DGPs) called “Data Management in Psychological Science: Specification of the DFG Guidelines”
They “suggest [. . .] that all external funding agencies consider these guidelines when deciding on grant proposals and when they review the final reports of research project” (p. 2)
They further state that “[…] with the publication of a manuscript, the person or group that collected the data (the “data sharers”) should make available all primary data necessary to reproduce the published results.” (p. 7)
“A publication should report all other variables measured within the study or studies that were not used for the publication itself”(p. 7)
- All data that were collected should be made available for publicly funded projects.
- For educational research, the discipline-specific memorandum on the Provision and Use of Quantitative Research Data in Educational Research (German only, Stanat, 2014) which was co-authored by psychological researchers proposes three different options for sharing research data:
- archiving by the data producer, data are provided on demand for verification of published results
- archiving by the data producer, data are provided on demand with extended documentation for secondary analyses
- deposition with a data archive
Bundesministerium für Bildung und Forschung, BMBF [Federal ministry of Education and Research]
Requirements of BMBF projects differ from case to case. For all projects, the BMBF requires a Verwertungsplan (“utilitzation plan”) that outlines how the potential of the collected data could be further exploited within:
Prospects of scientifical or technical success (with time horizon) should be described independently from prospects of economical success – among other things, how the planned results could be reused (e.g. in public tasks, databases, networks, transfer posts, etc. ). Also a possible collaboration with other institutions, companies, networks, research centers and others have to be included. (Bundesministerium für Bildung und Forschung, n.d.)
Moreover, some programs obligate researchers to deposit the project’s research data within a data archive (see this exemplary excerpt of an educational science program’s call):
The applicant commits him/herself to deposit the data, that was collected during the project, in reusable form within a suitable institution (e.g. GESIS-Leibniz institute for social sciences or a research data center) when the project is finished. This should be done with the goal of ensuring longterm data archiving, secondary analyses or reuse. There, data will be archived, documented and provided for the scientific community by request. (Bundesministerium für Bildung und Forschung, 2012)
Moreover, future BMBF projects of the Rahmenprogramm Empirische Bildungsforschung are required to deposit their data with the (German) platform Forschungsdaten-Bildung which provides checklists and guidance on data management related issues (e.g. on creating data management plans for educational research” (German only)).
EU (Horizon 2020)
Horizon 2020 incorporates an Open Research Data Pilot which will become the program’s default option in 2017. Researchers taking part in this pilot are required to write Data Management Plans (DMP) and to assure open access to their research data (if no legal or ethical concerns hinder data sharing).
Furthermore, the Guidelines on Data Management (European Commission, 2016) state that DMPs should be updated during the project (as necessary). Thus, data management plans are no longer just part of research projects at the proposal stage, but become project deliverables.
The publication of data is further outlined in the Guidelines on Open Access to Publications and Research Data.
- Bundesministerium für Bildung und Forschung. (n.d.). Richtlinien für Zuwendungsanträge auf Ausgabenbasis (AZA) – mit ergänzendem BMBF-Vordruck 0335 –. Retrieved november 9, 2016, from http://foerderportal.bund.de/easy/module/easy_formulare/download.php?datei=179
- Bundesministerium für Bildung und Forschung. (2012). Bekanntmachung vom 10. Oktober 2012. Retrieved from https://www.bmbf.de/foerderungen/bekanntmachung.php?B=774
- Bundesministerium für Bildung und Forschung. (2015). Bekanntmachung vom 12. Januar 2015. Retrieved from https://www.bmbf.de/foerderungen/bekanntmachung-1003.html
- DFG. (2015). Guidelines on the handling of research data. Retrieved from www.dfg.de/download/pdf/foerderung/antragstellung/forschungsdaten/guidelines_research_data.pdf
- European Commission. (2016). H2020 programme guidelines on FAIR data management in Horizon 2020. Retrieved from http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf
- Schönbrodt, F., Gollwitzer, M., & Abele-Brehm, A. (2016). Data management in psychological science: Specification of the DFG guidelines. Advance online publication. Retrieved from http://www.dgps.de/fileadmin/documents/Empfehlungen/Data_Management_in_Psychological_Science_20160928.pdf
- Stanat, Petra (2015). Bereitstellung und Nutzung quantitativer Forschungsdaten in der Bildungsforschung: Memorandum des Fachkollegiums „Erziehungswissenschaft“ der DFG [ on the Provision and Use of Quantitative Research Data in Educational Research: The DFG’s discipline-specific memorandum “Educational Sciences”]. Retrieved from www.dfg.de/download/pdf/foerderung/antragstellung/forschungsdaten/richtlinien_forschungsdaten_bildungsforschung.pdf
- The ELFI site disseminates information on funding opportunities in Germany.
- Katja Hartig and Volker Soßna published a working paper on the topic of research data management and DFG (German Research Foundation) funding applications. Hence, this paper is especially helpful for researchers that want to apply for funding via DFG.