Research data management (RDM)

RDM enables the establishment of standardized rules for handling research data in a project. The resulting systematic use of methods and tools creates more clarity and organization - data can be found and shared more easily, for example. This allows more time for important things such as your own research.

By creating a data management plan and developing and implementing it over the course of a research project, the requirements of third-party funders with regard to research data management are met.

Storing research data in repositories and long-term archives provides a secure way of preserving data and thus protects against unintentional data loss or misuse.

Research data management makes it possible to structure data even better, make it easier to understand, and prepare it with the help of metadata and digital tools. As a result, the data can be found and reused more easily.

Permanent citability and referenceability through so-called persistent identifiers increase one's visibility in the academic world.

Good research data management provides the researcher with evidence of independent scientific work as well as a methodologically correct procedure in accordance with the guidelines for ensuring good scientific practice of the University of Tübingen as well as the DFG.

By the use of services such as repositories, tools, persistent identifiers, and interoperable interfaces, research data management offers the possibility of easy reuse and sharing of selected data for possible follow-up projects, alone or with others, demonstrating a responsible and sustainable use of one's research data.

Good research data management provides legal compliance in regard to data protection, copyright, licensing and patent law by taking these aspects into account within the respective research project. In addition, measures in this context help to protect sensitive information such as personal data from unauthorized access.