Presentation about the reproducibility initiative at the University of Utah.
Presentation from Singapore Meeting on Research Integrity Reproducibility: Research integrity but much, much more.
A long list of papers with link to the code that supports the papers.
This presentation will review incentives for researchers to engage in reproducibility and data sharing practices and offer practical solutions for metadata, file handling, preservation, and licensing issues. It will focus on pragmatic motivations and methods for integrating reproducibility concepts into existing processes.
This presentation to LERU workshop: Nurturing a Culture of Responsible Research in the Era of Open Science considered the issue of the credibility of science being in question in a 'post-truth' world and how reproducibility is adding to the problem. Open Science offers a solution, but it is not easy to implement, particularly by research institutions. The main issues relate to language used in the open space, that solutions look different to different disciplines, that researchers are often feeling "under siege" and that we need to reward good open practice.
A fundamental challenge for open science is how best to create and share documents containing computational results. Traditional methods involve maintaining the code, generated tables and figures, and text as separate files and manually assembling them into a finished document. As projects grow in complexity, this approach can lead to procedures which are error prone and hard to replicate. Fortunately, new tools are emerging to address this problem and librarians who provide data services are ideally positioned to provide training. In the workshop we’ll use RStudio to demonstrate how to create a "compilable" document containing all the text elements (including bibliography), as well as the code required to create embedded graphs and tables. We’ll demonstrate how the process facilitates making revisions when, for example, a reviewer has suggested a revision or when there has been a change in the underlying data. We’ll also demonstrate the convenience of integrating version control into the workflow using RStudio’s built-in support for git.