At the end of the course, the students will have the fundamental notions of provenance, data curation and how they are interleaved with data science for addressing data-driven sciences problems with earth and biodiversity as examples.
The students will acquire the initial strategies to model provenance in data-driven experiments and use curation to track the information associated with their design and execution to promote explainability and reproducibility.
One crucial point is the emphasis given by the tutorial on the multidisciplinary nature of data science teams, as well as the importance of communication skills at a level where all team members are used to the terms and concepts used by other members.