  In modern data-driven science, reproducibility and reusability are key
challenges. Scientists are well skilled in the process from data to
publication. Although some publication channels require source code and data to
be made accessible, rerunning and verifying experiments is usually hard due to
a lack of standards. Therefore, reusing existing scientific data processing
code from state-of-the-art research is hard as well. This is why we introduce
CLAIMED, which has a proven track record in scientific research for addressing
the repeatability and reusability issues in modern data-driven science. CLAIMED
is a framework to build reusable operators and scalable scientific workflows by
supporting the scientist to draw from previous work by re-composing workflows
from existing libraries of coarse-grained scientific operators. Although
various implementations exist, CLAIMED is programming language, scientific
library, and execution environment agnostic.
