DFG’s Guidelines
Research data management plays a critical role in scientific research as it helps ensure the accuracy, reliability, and integrity of findings. The German Research Foundation (DFG) recognises the importance of responsible and ethical data management practices in scientific research and has provided guidelines for safeguarding good research practice.1
As a recipient of a DFG grant, the Collaborative Research Center (CRC) 1261 is required to adhere to this code of conduct. By following these guidelines, the CRC 1261 can maintain its reputation for high-quality scientific research and uphold the standards expected by the DFG.
Key points
Data should be collected, processed, and stored in a manner that allows for transparency and reproducibility.
Researchers should keep comprehensive and accurate documentation of their data and research processes.
Data should be stored in a secure and long-term accessible manner, and appropriate backup procedures should be in place.
Data should be made available to other researchers upon request, while respecting confidentiality and privacy concerns.
The integrity of data should be ensured through proper version control and a clear chain of custody.
Data should be properly cited and acknowledged in publications and presentations.
Researchers should be aware of and comply with relevant laws and regulations, such as those related to data privacy and intellectual property.
Open Data
Open data is a crucial aspect of research transparency and reproducibility. By making research data open and accessible, researchers can foster collaboration and knowledge exchange and facilitate the reuse of data for new purposes. The DFG strongly encourages researchers to openly share their data, ideally through publication in a research data repository.
In addition, Kiel University is committed to advancing open access to scientific research outcomes, as stated in its Guidelines for the Promotion of Open Access at Kiel University (german only).2 The university’s goal is to foster the dissemination of scientific discoveries while simultaneously enhancing the visibility and perpetual accessibility of publications authored by its faculty members.
Confidential Data
There may be some data that cannot be publicly shared for reasons such as privacy, security, or intellectual property. These data should be kept confidential and access should be restricted to only those who have a legitimate need to access the information. It is important to assess the sensitivity of the data and to implement appropriate measures to ensure its protection.
FAIR Data
The DFG promotes the principles of FAIR (Findable, Accessible, Interoperable, Reusable) data in research. FAIR data ensures that research results are transparent, accessible, and reusable for other researchers and stakeholders, improving the reliability and reproducibility of scientific findings. The DFG encourages researchers to adopt FAIR data principles in their data management practices and to make their research data openly available, wherever possible. The implementation of FAIR data principles helps to advance scientific discovery and enables new and innovative research approaches.
Note
While FAIR data does not need to be open, the metadata describing the data must be open in order to comply with the FAIR principles.
How to adhere to the FAIR data principles
Adhering to the FAIR data principles entails embracing several key guidelines:
Findable: Data must be assigned a unique and persistent identifier, such as a digital object identifier (DOI), and should be searchable and discoverable through metadata and catalogs.
Accessible: Data must be accessible and retrievable through standard mechanisms, such as HTTP, and should include information on access conditions, fees, and any necessary authentication or authorisation procedures.
Interoperable: Data must use open and standard data formats, metadata, and APIs to allow for easy integration and reuse with other data sets.
Reusable: Data must include clear and comprehensive metadata, as well as appropriate licenses and rights statements, to enable re-use, analysis, and integration with other data sets.
In addition to these principles, it is important to have a clear and comprehensive data management plan that outlines the steps for acquiring, documenting, storing, and sharing data in a way that is FAIR. This includes considerations such as data backup and preservation, as well as ethical and legal aspects of data sharing.