Data Audit as a Way to Prevent/Contain Misconduct

Abstract

Research misconduct is frequently in the media headlines. There is consensus among leading experts on research integrity that the prevalence of misconduct in research is at least 1%, and shoddy work may even go over 5%. Unfortunately, misconduct in research impacts all walks of life from drugs to human subject protections, innovations, economy, policy, and even our national security. The main method of detecting research misconduct depends primarily on whistleblowers. The current regulations are insufficient since dependence on whistleblowers manifests itself as an accidental hit or miss. No other endeavor in our society depends on such a poor system of discovery of misconduct to remedy it. Nearly a quarter of a century ago, I proposed data audit as a means to prevent/contain research misconduct. The audit has to protect the creative process and be non-obtrusive. Data audit evaluates the degree of correspondence of published data with the source data. The proposed data audit does not require any changes in the way researchers carry out their work.

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