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Best practices for improving the computational reproducibility of research (ASIS&T)

Online • Free
About this webinar

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 libraries can advance reproducibility through adoption of new tools and approaches for researchers that help prepare and publish code and data 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.

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April Clyburne-Sherin

Outreach Scientist

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.

Travis Hewgley

Director of Institutional Partnerships

Travis Hewgley currently serves as the Director of Institutional Partnerships collaborating with academic institutions and universities at Code Ocean. Prior to Code Ocean, Travis has held institutional sales leadership roles with some of the leading educational technology providers and publishing companies including Cambridge University Press, McGraw-Hill and Oxford University Press.