Skip to Main Content
UNLV Logo

Research Data Management

Reproducibility Crisis

An famous 2016 article in Nature reported on a survey of 1500 scientists and begin with the alarming statement open statement that "More than 70% of researchers have tried and failed to reproduce another scientist's experiments, and more than half have failed to reproduce their own experiments." While this has led to terms like the "Replication" and "Reproducibility" crisis, it has also led to better Open Science methods, tools, and resources. 

"1500 scientists lift the lid on reproducibility," by Monya Baker, Nature (2016)

Replication vs Reproducibility

While "Replicability" vs "Reproducibility" are often used interchangably, here is a helpful distinction: 

  • Reproducibility” refers to the ability of a researcher to duplicate the results of a prior study using the same materials and procedures as were used by the original investigator. 
  • Replicability” Replicability refers to the ability of a researcher to duplicate the results of a prior study if the same procedures are followed but new data are collected

Credit: NSF Report of the Subcommittee on Replicability in Science

Data Management, Open Sciences, and Reproducibility

Promoting reproducibility in research requires adopting a range of practices, many of which are part of open science. Open science refers to efforts that make research more transparent, accessible, and inclusive. While open science often focuses on sharing tools and research, this can only be done well with good data management practices in place.  The RDM Best Practices tab provides help steps to incorporate into your research workflow and few are additional resources for contributing to Open Science. 

Computational Tools

Additional Reading

© University of Nevada Las Vegas