Reproducible Research Can Still Be Wrong: Adopting a Prevention Approach

TL;DR

This paper emphasizes that reproducibility and replicability are vital for scientific integrity but are often compromised, advocating for a preventative approach through enhanced data analysis education and software tools to address these issues.

Contribution

It proposes a preventative strategy to improve reproducibility and replicability in science by expanding data analysis education and routine use of software tools.

Findings

Reproducibility and replicability are crucial for scientific progress.

Current crisis undermines confidence in scientific results.

Preventative measures can enhance research integrity.

Abstract

Reproducibility, the ability to recompute results, and replicability, the chances other experimenters will achieve a consistent result, are two foundational characteristics of successful scientific research. Consistent findings from independent investigators are the primary means by which scientific evidence accumulates for or against an hypothesis. And yet, of late there has been a crisis of confidence among researchers worried about the rate at which studies are either reproducible or replicable. In order to maintain the integrity of science research and maintain the public's trust in science, the scientific community must ensure reproducibility and replicability by engaging in a more preventative approach that greatly expands data analysis education and routinely employs software tools.