Research Data Management (RDM) is a crucial step for all fields of science relying on data, no matter if medium size, large or huge amounts of data. SCC provides know-how and infrastructure for proper data management that helps with every-day data handling as well as large-scale data workflows according to the F.A.I.R. principles and scientific community standards.
It is about defined data life cycles, organization of research data in teams, data sharing and data publications. The CASUS RDM is governed by the FAIR principles. We provide consultation to application field scientists in all questions related to RDM, offer services for practical RDM, and develop new and tailored solutions for RDM based on state-of-the-art methods and software.
DataLad is a tool for data version control and machine-actionable reproducibility on top of git an git-annex. See the DataLad handbook for many more details.
Unfortunately, the DataLad reproducibility via
datalad run / rerun
is incompatible with HPC-style batch processing. Our DataLad plugin for Slurm support solves this conflict and enables DataLad to HPC. See our pre-print paper for more details.
Dr. Andreas Knüpfer
Dr. Timothy Callow (formerly)
Franz Pöschel