Using Code Ocean in the Sciences and Engineering: Bringing computational reproducibility to your research collaborations

Computational analyses are playing an increasingly central role in research. However, many researchers have not received training in best practices and tools for reproducibly managing and sharing their code and data. This is a step-by-step, practical workshop on managing your research code and data for computationally reproducible collaboration. 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 organizing their files, automating their analyses, documentation, and submitting their code and data for publication. Although workshop participants will be using the Code Ocean platform, the exercises and best practices are platform and discipline agnostic. 

Register here: 

Learning Objectives:

·        Learn best practices for file organization, documentation, automation, and dissemination.

·        Assess possible tools for managing code and data.

·        Build a collaborative workspace for your code and data on Code Ocean.

·        Learn to reuse a pre-configured compute capsule based on a project in your field of research.


Code Ocean at Princeton is co-sponsored by Princeton University Library, Princeton Institute for Computational Science and Engineering (PICSciE), Center for Statistics and Machine Learning, Data-Driven Social Science Initiative, Princeton Neuroscience Institute, and Princeton Research Computing.