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Research Reproducibility: Education and Practice

“Reproducibility is important not because it ensures that the results are correct, but rather because it ensures transparency and gives us confidence in understanding exactly what was done.” - Roger Peng (2014), Johns Hopkins University, Professor of Biostatistics. (1)

Enabling reproducible research - as in the ability to reproduce reported results through the re-analysis of the original data and code - is incredibly important but also not a simple thing to accomplish. When more than 70% of researchers have tried and failed to reproduce another scientist’s experiments (and more than half fail to reproduce their own) (2), it is important to teach both new and experienced researchers how to engage in data management practices and use new tools and methods that make their research methods transparent, and results reproducible. The Center for Data and Visualization Sciences has invited a panel of four scholars to discuss how to engage in reproducible research practices, make use of tools to aid in the process, and help educate the next generation of scholars.

Panelists include:

  1. Steven Grambow, Ph.D, Assistant Professor of Biostatistics and Bioinformatics
  2. Angela Zoss, Ph.D, Assessment and Data Visualization Analyst, Duke University Libraries
  3. Robert Schick, Ph.D., Research Scientist, Marine Science and Conservation, Nicholas School for the Environment
  4. Maria Tackett, Ph.D., Assistant Professor of the Practice of Statistical Science

Lunch will be provided

  1. https://simplystatistics.org/2014/06/06/the-real-reason-reproducible-research-is-important/
  2. https://www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970

Related LibGuide: Research Data Management by Jen Darragh

Friday, November 22, 2019
12:00pm - 1:00pm
Bostock 127 (The Edge Workshop Room)
West Campus
Data and Visualization   Public Event  
Registration has closed.

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Center for Data and Visualization Sciences