Caching and Reproducibility: Making Data Science Experiments Faster and FAIRer

« Small to medium-scale data science experiments often rely on research software developed ad-hoc by individual scientists or small teams. Often there is no time to make the research software fast, reusable, and open access. The consequence is twofold. First, subsequent researchers must spend significant work hours building upon the proposed hypotheses or experimental framework. In the worst case, others cannot reproduce the experiment and reuse the findings for subsequent research. (…) »

source >, Moritz Schubotz, Ankit Satpute, André Greiner-Petter, Akiko Aizawa, Bela Gipp, 22 avril 2022,