Don’t review articles that withhold data

Journal editors can enforce replication policies. Authors can decide to work transparently. Most initiatives for open science and reproducibility agree that editors and authors are  are the key actors to enforce the gold standard of research integrity. However, peer-reviewers can use their leverage as well: just say you will only review an article once the author provides the data.

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Guest Post: Archive your data or they die with you, by Thomas Leeper

Thomas Leeper is a political scientist at Aarhus University and focuses on public opinion, political psychology, and experimental methods. I invited him to write a guest post because he is a contributing developer for the rOpenGov and rOpenSci open source software projects. He also wrote the very useful dvn package that connects the statistical software R and the data archive Dataverse. In his post, Leeper explains why there is no reproducibility without proper data archiving.

Replication Workshop: What frustrated students the most, and why they still liked the course

The Cambridge Replication Workshop 2013/14 just finished. In eight sessions, graduate students replicated a published paper and learned about reproducibility standards. This is a summary of student feedback on data transparency and the course itself. Some were extremely frustrated, a few dropped out, and those who stayed found the course “fantastic” and “incredible”.

Quality checks in data repositories – how feasible?

I recently posted a list of data repositories that facilitate reproducibility. I now came across a specialized data archive at Yale. This one seems different: it aims at verifying code and data that are submitted. Is such quality control feasible?