ReproNim and the ReproPub: Establishing Best Practices for the Re-executable Publication

[dnkennedy]

ReproNim and the ReproPub: Establishing Best Practices for the Re-executable Publication

David N. Kennedy, University of Massachusetts Medical School

Collaborators
JB Poline
Yaroslav Halchenko
Satra Ghosh
David Keator
Jeff Grethe
Maryann Martone
Nina Preuss
Al Crowley
Matt Travers
Christian Haselgrove
Julie Bates
Dorota Jarecka

Github Link (if applicable)
https://github.com/ReproNim

Abstract (max. 200 words):
There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generalizes across changes in the processing approach, and sampled population, in a controlled scientific fashion. ReproNim: A Center for Reproducible Neuroimaging Computation is a recently funded initiative that seeks to facilitate the ‘last mile’ implementations of core re-executability tools in order to reduce the accessibility barrier and increase adoption of standards and best practices at the neuroimaging research laboratory level. In this report, we summarize the overall approach and tools we have developed in this domain.

Preferred Session
Open science in policies and regulations

Additional Context
DOI: 10.31219/osf.io/u78a6

[dnkennedy]

Hi Tim. This is a starting placeholder. Will update the details a little further later, but wanted to get something in...