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Best Practices for Improving the Computational Reproducibility of Research

With the aim of improving the computational reproducibility of the research they publish and fund, journals and funders are increasingly calling for published research to include associated data and code. However, computational reproducibility has long been time-consuming and technically challenging to achieve for researchers. Institutions and researchers can advance reproducibility through adoption of new tools and practices to prepare their research for easy reuse.

In this webinar, we introduce reproducibility best practices and resources that are applicable across disciplines. Finally, we will demonstrate tools that help researchers overcome barriers to reproducibility including how to share their code and data using Code Ocean.


April Clyburne-Sherin

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 focused on creating curriculum and running workshops for scientists in open and reproducible research methods (Center for Open Science, SPARC) and is co-author of FOSTER's Open Science Training Handbook

Sponsored by ASIS&T.