Highlights of the US National Academies Report on “Reproducibility and Replicability in Science”

Harvey Fineberg,Victoria Stodden,Xiao-Li Meng

doi:10.1162/99608f92.cb310198

Harvey Fineberg, Victoria Stodden + Show 1 more

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https://doi.org/10.1162/99608f92.cb310198

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Abstract

In 2019, the National Academies of Sciences, Engineering, and Medicine of the United States released a report on reproducibility and replicability in science. This topic is of keen interest to everyone concerned with the reliability of scientific research and the role of computational and statistical analysis in science. In this interview conducted by Xiao-Li Meng, (HDSRâs Editor-in-Chief), report committee chairÂ Harvey Fineberg (President of the Gordon and Betty Moore Foundation) and committee member Victoria Stodden (Associate Professor in the School of Information Sciences at the University of Illinois, Urbana-Champaign) recount the aims and deliberations of the committee, its major recommendations, and calls for concerted efforts from data scientists, research scientists, funding agencies, academic institutions, professional journals, and journalists to ensure scientific rigor and public trust in science.

Highlights

In 2019, the National Academies of Sciences, Engineering, and Medicine of the United States released a report on reproducibility and replicability in science
In this interview conducted by Xiao-Li Meng, (HDSR’s Editor-in-Chief), report committee chair Harvey Fineberg (President of the Gordon and Betty Moore Foundation) and committee member Victoria Stodden (Associate Professor in the School of Information Sciences at the University of Illinois, Urbana-Champaign) recount the aims and deliberations of the committee, its major recommendations, and calls for concerted efforts from data scientists, research scientists, funding agencies, academic institutions, professional journals, and journalists to ensure scientific rigor and public trust in science
Reproducibility and replicability differ in the type of results that should be expected: when a researcher transparently reports a study and makes available the underlying digital artifacts, such as data and code, the results should be computationally reproducible at that time, at least on the same system

Summary

Introduction

In 2019, the National Academies of Sciences, Engineering, and Medicine of the United States released a report on reproducibility and replicability in science. Replication encompasses a broad range of issues in scientific practices, reporting of empirical and other steps taken in the research, and statistical methods, including calculation of p-values and criteria for statistical significance.

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