Brought to you by NumFOCUS Foundation and O’Reilly Media
The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY

Preparing your Jupyter notebook for computationally reproducible publication: A hands-on BYONotebook tutorial for researchers

April Clyburne-Sherin (Code Ocean)
9:00am–12:30pm Wednesday, August 22, 2018
Average rating: ***..
(3.00, 2 ratings)

Who is this presentation for?

  • Researchers who use Jupyter notebooks in their research and wish to share them, research support professionals, and anyone interested in open science or reproducibility

Prerequisite knowledge

  • A basic understanding of how to create and run a Jupyter notebook

Materials or downloads needed in advance

  • A laptop (If you want to work with your own Jupyter notebook, make sure it is in running order; example notebooks will be provided to those who do not wish to use their own.)

What you'll learn

  • Understand best practices for organization, documentation, and sharing
  • Learn how to apply FAIR Principles to your research, assess possible tools for publishing notebooks, and submit your notebook for publishing on Code Ocean


April Clyburne-Sherin walks you through preparing Jupyter notebooks for computationally reproducible publication. You’ll learn best practices for publishing notebooks and get hands-on experience preparing your own research for reuse, creating documentation, and submitting your notebook to share.


Essential information about computational reproducibility

  • Computational reproducibility and its relevance to researchers
  • Examples of computationally reproducible research

Preparing your data for publication

  • Best practices for data documentation
  • Examples of well-documented datasets

Preparing your Jupyter notebook for publication

  • Best practices for sharing
  • How to prepare your notebook to be used by others

Documenting your research for reuse

  • Best practices for documentation
  • The FAIR Principles for discoverable research
  • The minimum documentation for reuse (a README file, essential metadata, etc.)
  • Choosing a license

Sharing your Jupyter notebook

  • Available tools and best practices for publishing notebooks
  • Submitting your notebook for publishing on Code Ocean

Integrating reproducibility into your research workflow

  • Best practices for improving reproducibility throughout the research workflow
  • Available tools to support reproducibility
Photo of April Clyburne-Sherin

April Clyburne-Sherin

Code Ocean

April Clyburne-Sherin is an outreach scientist at Code Ocean, where she trains scientists in computational reproducibility best practices. An epidemiologist, methodologist, and expert in open science tools, methods, training, and community stewardship, since 2014, April has focused on training scientists in open and reproducible research methods at the Center for Open Science, Sense about Science, and SPARC. She is coauthor of FOSTER’s Open Science Training Handbook; cofounder of OOO Canada, a network to promote leadership in open access, open education, and open data; and producer of The Method, an open source podcast. She holds an MS in population medicine (epidemiology).