Submit application & planning
Many applications for third-party funding require a strategy for research data management: data should be stored in a traceable manner. This should enable third parties to perform a secondary evaluation or subsequent use. A data management plan is the central document for this. We provide support for various types of funding applications, including those for DFG, Horizon Europe, and NFDI.
Research data are all analog and digital data generated during your research project. Existing data, so-called secondary data, can be reused. New data, also known as primary or raw data, can be collected. Data can therefore be the basis or the result of the research process. Different research methods of individual scientific disciplines produce different types and formats of data. Hence, there are specific requirements for research data management depending on the method and discipline.
Research data management (RDM) is the organization and management of data, as well as all measures to sustain data usability. Sustainable RDM aims to collect, store, and document research results using subject-specific standards. Making data available for subsequent use is optional but often encouraged.
Increasingly, research data management (RDM) is an essential requirement in research projects for funders and publishers. Structured data management before, during, and after the research project has additional advantages: Metadata and archiving, core aspects of RDM, ensure traceability, reproducibility, data security, and versioned backups.
Do you need an RDM strategy for your external funding application? For specific questions, e.g. on DFG applications, we will gladly advise and support you. Contact us at researchdata(at)tum.de!
Data management plan
In a data management plan (DMP), you describe how you will handle your research data during and after the end of the research project. This planning is often relevant for third-party funding.
You can find more info in our handout about creating a DMP.
Working ethically with data
Data ethics is concerned with developing and implementing principles, including privacy, inequality, transparency, bias, and environmental damage and data sustainability. The Ethical Data Initiative, jointly coordinated by the University of Exeter and the TUM Think Tank, fosters open discussions on data ethics and offers consultation, training, and resources on ethical aspects.
Get in touch!
For questions regarding application and planning, please feel free to contact us at researchdata(at)tum.de!
Further information: Store & manage data, Data analysis, Archive data, Publish & share data, Reuse data