Research data is one of the most important resources in science and requires a particularly high level of attention to ensure good scientific practice. Therefore, sustainable research data management (RDM) is the foundation for current and future research.
For this reason, one goal of SFB 1280 is to ensure that research data are findable, accessible, interoperable, and reusable in accordance with FAIR principles, which is reflected in the SFB’s Research Data Policy.
With the start of the second funding period of SFB 1280, all RDM activities in the SFB are centrally coordinated by the Central Research Data Management (INF) project. In close consultation with the Data Management Board of the SFB, the INF project supports the researchers in improving their daily RDM routines and develops a sustainable and innovative RDM strategy together with the researchers.
In addition, the INF project organizes workshops on RDM relevant topics (e.g. Brain Imaging Data Structure) and regular Lab-Data-Cleaning-Days in the SFB to further sensitize researchers for the management of their research data.
All RDM activities of the SFB 1280 are networked with international RDM communities in the field of neuroscience and are carried out in close collaboration with the Open Science working group of the SFB and the central research data management working group of the RUB.
For example, the INF project supports the development of the RUB’s own research data repository as a use case for the SFB and develops workflows for it that allow the management of research data and metadata and their quality assurance. The goal is to secure the data for 10 years according to DFG specifications and, whenever possible according to data protection regulations, to publish it with a Persistent Identifier (PID).
Quicklinks
For more information or detailed advice on research data management in SFB 1280, please contact Marlene Pacharra (sfb1280data@rub.de), Research Data Steward in SFB 1280.
Otto, T., Rose, J. (2023) The open toolbox for behavioral research. Behav Res
Diers E, Pacharra M, Merz CJ, Ernst TM, Otto T (2023) Subject Code Generator v1.1 (v1.1). Zenodo.
Otto T, Wolf OT, & Merz C. (2023). EDA-Analysis App (5.11). Zenodo.