Preparing your data and code for computationally reproducible publication: A hands-on workshop for researchers

When

Thursday, April 5, 2018
10:00am - 12:00pm

2018-04-05 10:00:00 2018-04-05 12:00:00 America/New_York Preparing your data and code for computationally reproducible publication: A hands-on workshop for researchers Multimedia Seminar Center at the D. H. Hill LibraryD. H. Hill LibraryMultimedia Seminar Center at the D. H. Hill Library2 Broughton Dr. Campus Box 7111 Raleigh, NC 27695-7111

Where

  • Multimedia Seminar Center at the D. H. Hill Library
    D. H. Hill Library
    Multimedia Seminar Center at the D. H. Hill Library
    2 Broughton Dr.
    Campus Box 7111
    Raleigh, NC 27695-7111

Workshop Description

Computational analyses are playing an increasingly central role in research. Journals, funders, and other researchers are calling for published research to include associated data and code. However, many researchers have not received training in best practices and tools for sharing code and data. This is a step-by-step, practical workshop to prepare research code and data for computationally reproducible publication. The workshop starts with some brief introductory information about computational reproducibility, but the bulk of the workshop is guided work with code and data. We cover the basic best practices for publishing code and data. Participants move through organizing their files, creating a codebook, preparing their code for reuse, documentation, and submitting their code and data to share using Code Ocean.


Preparation:

  • Bring a laptop to fully participate.
  • Participants may bring their own data and code to work through during the workshop.
  • Participants should be able to successfully run the code they bring themselves. If you don't have code and data of your own to bring, you will follow along with example code and data
Workshop goals:
  • Define computational reproducibility and its relevance to researchers.
  • Learn best practices for file organization, documentation, and sharing.
  • Apply FAIR Principles to your research.
  • Assess possible tools for publishing code and data.
  • Submit your code and data for publishing on Code Ocean.
About the instructor:
April Clyburne-Sherin 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 training 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 of Outreach Scientist, she trains scientists in computational reproducibility best practices using Code Ocean.



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