This is a step-by-step, practical workshop on how to prepare research code and data for computationally reproducible publication. The workshop
starts with some brief introductory information about computational reproducibility, but the bulk of the workshop is guided work with code and
data. Participants move through best practices for organization, documentation, automation and dissemination of research data and code
using Binder and JupyterLab - free, open source technologies.
1. Understand the barriers to reuse of published research code and data.
2. Practice organizing, documenting, automating, and disseminating reproducible code and data.
3. Explore and assess tools and resources to aid reproducible publication.
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.