Research Data Management
What is research data?
"Research data includes measurement data, laboratory values, audiovisual information, texts, survey or observation data, methodological test procedures and questionnaires. Compilations, software and simulations can equally represent a central result of scientific research and are therefore also included under the term research data." See: DFG: Handling of research data
Research data management (RDM) includes the steps from the application planning of a research project, working with research data in everyday research to the publication and sustainable reuse of data.
In 2016, the "FAIR Guiding Principles for scientific data management and stewardship" were published in "Scientific Data" [1]. The authors intended to provide guidelines to improve findability, accessibility, interoperability, and reuse of digital data. The principles focus is on the machine readability of digital (meta)data.
The management of research data is now part of scientific work. As a measure of how data has been made available, greater account should be taken of the FAIR principles in the collection, use and storage of data.
Make data FAIR
- Findable data is indexed in a searchable resource and tagged with a Persistent Identifier (PID), such as a DOI
- Accessible data is described with rich metadata and stored in an open format
- Interoperable data uses a controlled vocabulary and contains references to other (meta)data
- Reusable data is linked to its provenance and released with an open license.
- Leibniz Association: Guidelines on the Handling of Research Data within the Leibniz Association
- DFG: Handling of Research Data
- HORIZON EUROPE: Open Research Data and Data Management Plans
Research data at WIAS
WIAS has adopted its own research data policy, which describes the handling of research data in accordance with good scientific practice:
WIAS Research Data Policy »
Further guidelines for handling research data:
