Reproducibility on a Platter

This talk, given at the FORCE2018 meeting in Montreal, introduces the reproducibility initiative of the Canadian Open Neuroscience Platform (www.conp.ca). CONP offers a flexible and reproducible approach to publishing academic research, combining transparency, data curation and code sharing to create the reproducible paper of the future. Our main goal is to share analyses in a way that lets readers replicate key figures from a journal article, as well as modify the code of the analyses to explore the impact of arbitrary parameters on those figures. To make it easier to re-run a research analysis, CONP integrates containers, data queries and Jupyter notebooks. Instead of acting as a replacement to traditional journal publishing, the CONP initiative will produce a complementary publication focused on analytical reproducibility and sharing. For each study published through CONP, our team will work with the authors to select elements of the study that capture the most important results and facilitate reproduction and exploration by reviewers and readers. We envision that our pipelines will become the standard in peer-review and remove the overhead that comes with accessing other lab’s data and running their analysis code.