Reproducibility and Provenance

Reproducible workflows increase research efficiency, accelerate collaboration and increase trust in science.
Image credit: NCEAS Learning Hub

Description

In most cases, the methods sections of papers are inadequate to fully reproduce the work described in the paper. By looking at a figure on a paper, we only get part of the story of how the scientist got to make this plot. This lesson introduces de concepts of computational reproducibility and provenance and gives an overview of how they can be achieved in your work.

{< fa check >}} Prerequisites

None

Learning Goal

• Discuss the concept of reproducible workflows, including computational reproducibility and provenance metadata
• Introduce tools and techniques for reproducibility supported by the NCEAS and DataONE

Duration

30 min