Process / pipelineethical-violations

Data Fabrication and Falsification

Data fabrication and falsification are serious forms of research misconduct involving intentional misrepresentation of research data. Fabrication means inventing data that were never actually collected; falsification means altering authentic data to change the meaning. Both undermine scientific integrity, waste research resources, and can harm research subjects and the public. Federal policy (42 CFR Part 93) formally defines these violations; detection is improving through statistical analysis tools and data transparency practices; prevention requires robust data governance and culture of accountability.

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Sources

  1. U.S. Office of Research Integrity. (2005). Public Health Service Policy on Research Misconduct. 42 CFR Part 93. Definitions of fabrication and falsification. link
  2. Carlisle, J.B. (2017). Data Fabrication and Deviation in Statistics in Anesthesia Articles. Anesthesia, 72(2), 221–237. DOI: 10.1111/anae.13603
  3. Nuijten, M.B., Hartgerink, C.H., van Assen, M.A., et al. (2015). The Prevalence of Statistical Reporting Errors in Psychology (1985-2013). Behavior Research Methods, 48(4), 1205–1226. DOI: 10.3758/s13428-015-0664-2

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Referenced by

ScholarGateData Fabrication and Falsification (Definition, Detection, and Prevention of Research Data Fabrication and Falsification). Retrieved 2026-06-04 from https://scholargate.app/en/research-ethics/data-fabrication-falsification