Tutorial

The Importance of Reproducible Science

Authors: Megan A. Jones

Last Updated: Oct 7, 2020

Verifiability and reproducibility are among the cornerstones of the scientific process. They are what allows scientists to "stand on the shoulder of giants". Maintaining reproducibility requires that all data management, analysis, and visualization steps behind the results presented in a paper are documented and available in full detail. Reproducibility here means that someone else should either be able to obtain the same results given all the documented inputs and the published instructions for processing them, or if not, the reasons why should be apparent. From

## Learning Objectives At the end of this activity, you will be able to:
  • Summarize the four facets of reproducibility.
  • Describe several ways that reproducible workflows can improve your workflow and research.
  • Explain several ways you can incorporate reproducible science techniques into your own research.

Getting Started with Reproducible Science

Please view the online slide-show below which summarizes concepts taught in the Reproducible Science Curriculum.

A Gap In Understanding

Image of a Twitter post submitted by Tracy Steal highlighting the obstacles slowing adoption of reproducible science pratices. These are: People are unaware there is a problem, 100% reproducibility is hard, One workflow does not fit all, Lack of motivation, and are scared of intial time investments.
Obstacles slowing adoption of reproducible science practices. Source:

Reproducibility and Your Research

Graphic showing the spectrum of reproducibility for published research. From left to right, left being not reproducible and right being the gold standard, we have publication only, publication plus code, publication plus code and data, publication with linked and executable code and data, and full replication.
Reproducibility spectrum for published research. Source: Peng, RD Reproducible Research in Computational Science Science (2011): 1226鈥�1227 via

How reproducible is your current research?

**Thought Questions:** Have a look at the reproducible science check list linked, above and answer the following questions:
  • Do you currently apply any of the items in the checklist to your research?
  • Are there elements in the list that you are interested in incorporating into your workflow? If so, which ones?

Additional Readings (optional)

  • Nature has collated and published (with open-access) a special archive on the .
  • The Nature Publishing group has also created a for its authors that focuses primaily on reporting issues but also includes sections for sharing code.
  • Recent open-access issue of focusing on reproducible ecology and software packages available for use.
  • A nice short blog post with an annotated bibliography of "Top 10 papers discussing reproducible research in computational science" from Lorena Barba: .

Questions?

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