Critical Data Studies: Reproducibility and Renku

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Description

This lecture covers the importance of reproducibility in data science, focusing on the origins of the scientific method and the current crisis of reproducibility in research. It also introduces Renku, a platform for managing data-driven projects. The lecture discusses the technical stack needed for reproducibility, policy implications of open science, and the FAIR principles. Students are guided on how to use Renku for their projects and the tools available for ensuring reproducibility.

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