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How to bring computational reproducibility to your journal

Online • Free
About this webinar

Researchers develop code, algorithms, and analyses in a variety of programming languages, but these materials are rarely curated to be executable. This presents a barrier to other researchers who seek to understand or reuse that work.  Providing all research artifacts — code, data, protocols — is critical for enabling reproducibility, advancing research discoveries and providing value to end users.

This 30-minute webinar demonstrates how Code Ocean, an executable code repository, allows researchers to deposit not only their code but also the dependencies that their code relies on — and get a DOI for the published “compute capsule.” By using container technology, Code Ocean supports execution across programming languages, versions and operating systems, requiring nothing besides a web browser on the user’s part.

Get an inside look at the platform, and how Code Ocean can — or already does — fit within your journal’s publication workflow.
We explore how to:

  1. Move beyond the PDF with embeddable code
  2. Increase your publication’s impact through reproducibility
  3. Provide more benefits and functionality for your authors
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Pierre Montagano

Director of Business Development, Code Ocean

Pierre leads sales and business development for Code Ocean, a cloud-based computational reproducibility platform that provides researchers and developers easier ways to share, discover and run code published in academic journals and conferences. Prior to Code Ocean, Pierre was the director of sales at Squid Solutions, a usage analytics company that enables publishers to become more data-driven by providing an open-source solution for building analytics apps. He has held both product marketing and sales leadership positions with some of the world’s leading scientific and education publishing companies including Pearson, McGraw-Hill and Cambridge University Press.

Seth Green

Developer Advocate, Code Ocean

As Developer Advocate, Seth is the liaison between scientists (Code Ocean’s developers) and the product/team; he helps authors get their code up and running on the platform and also tries to represent their interests in internal discussions. He did undergrad at Swarthmore and a few years of a Ph.D. program at Columbia, which he left with a masters degree in 2015.