Research data management

Data management and research funding

Research data management (RDM) involves handling research data methodically and systematically. Handling data efficiently involves planning and implementing data analysis, storage, archiving and publication, as well as establishing standard practices.

RDM has become central to science policy during the last few years and is also a requirement and supported by major funding providers such as the Federal Ministry of Education and Research (BMBF), the European Research Council or the German Research Foundation (DFG). Detailed planning and characterization of research data management not only prevents data loss and increases the visibility, effectiveness and sustainability of your research, it also increases the chances of receiving funding.

Research data are a valuable resource in science. Handling this data in a responsible manner is decisive for preserving and transferring research findings, which, in turn, encourages scientific progress. Professional research data management offers many advantages to researchers, the users of this data and society as a whole and strengthens research activity.

FAU Competence Center Research Data and Information (FAU CDI)

The FAU Competence Center Research Data and Information (FAU CDI) was established as a central research institution in order to provide support to all researchers at the University and at Uniklinikum Erlangen with questions and tasks regarding research data management and the CRIS Research Information System.

This support includes providing advice with funding applications as well as special services for handling research data. In addition, FAU CDI is also directly involved in research projects.

FAU CDI collaborates closely with other organizational units:

Please write an e-mail to forschungsdaten@fau.de if you have any questions about research data management.

FAU believes that storing and managing research data is crucial for successful, sustainable research and scientific integrity. It is essential that research data are handled responsibly and methodically. If the University, its members and the general public are to benefit, this must not only be encouraged but also made a requirement. To achieve this, it is important to raise awareness of research data and FAIR principles in the long term.

FAU’s Research data policy contains guidelines for all staff on how to handle research data. It is updated at regular intervals and passed by the Executive Board of the University. The current version is available at Research data policy.

Planning effective research data management (RDM) fulfills the requirements of good scientific practice (GSP) and the guidelines of the DFG. The aim of these guidelines is to promote a culture of academic integrity, which is vital for trustworthy science.

Good RDM strategies increase the chances of receiving funding, since many funding organizations, public funding providers (such as theDFG and, for example, the European Union forERC applications) and foundations require a data management concept during the application phase. The aim of this is to ensure that both science and society receive optimum benefit from the funding and that the data and results of the research remain accessible to the public after the project has been completed where possible.

Discipline-specific recommendations and solutions for the sustainable development and utilization of research data are being developed by the consortia of the publicly funded National Research Data Infrastructure (NFDI) in particular. The standards these recommendations contain will influence how various disciplines deal with research data in the future.