This is a guide from Stanford University outlining methodology, tools, and resources for increasing reproducibility in science.

This LibGuide from the University of Utah outlines some first steps, tutorials, and toolkits related to making research reproducible, with a strong focus on quantitative and computational research.

This blog post is apart of the Love Your Data campaign #LYD16, a global and cross-institution awareness campaign for open data, research reproducibility, and research data management. This post features ReproMatch and ReproZip as important tools for achieving reproducibility.