Although journals and funders are calling for published research to include data and code, many researchers have not received training in best practices and tools for sharing. This workshop address this gap while also providing those who support researchers with curated best practices. In a practical, step-by-step design comprised of hands-on exercises, participants prepare research code and data for computationally reproducible collaboration and publication. Although the workshop starts with a brief introduction to computational reproducibility, the bulk of the workshop is guided work with data and code. Participants move through organizing, documenting, automating, and submitting code and data for reuse. Tools to support reproducibility are introduced but all lessons will be platform agnostic.
April is an epidemiologist, methodologist, and expert in open science tools, methods, training, and community stewardship. She holds an MS in Population Medicine (Epidemiology). Since 2014, she has focussed on creating curriculum and running workshops for scientists in open and reproducible research methods (Center for Open Science, Sense About Science, SPARC) and is co-author of FOSTER's Open Science Training Handbook. In her current role as Outreach Scientist at Code Ocean, she trains scientists in computational reproducibility best practices.