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.
Find Topic with PaperMindSoonVideoSoon
Read the full method
Members only
Sign inSign in with a free account to read this section.
Sources
- U.S. Office of Research Integrity. (2005). Public Health Service Policy on Research Misconduct. 42 CFR Part 93. Definitions of fabrication and falsification. link ↗
- Carlisle, J.B. (2017). Data Fabrication and Deviation in Statistics in Anesthesia Articles. Anesthesia, 72(2), 221–237. DOI: 10.1111/anae.13603 ↗
- 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 ↗