Forensic scientometrics is a new field focussed on more detailed and in-depth investigations of research & research articles with a particular focus on detecting fraud and questionable research practices.
The problem
The journal business models and outdated incentive system in academia are encouraging questionable research practices and fraud. Peer review was not designed to detect fraud or manipulated data and fails to do so regularly. This significantly undermines research, erodes trust and can even result in entire fields of research and funding that is based on fraud1.
The solution
Post-publication peer review offers many benefits, including more experts commenting on a research output. However, to truly combat issues of fraud, data manipulation and fake content, we need to investigate research outputs in a more forensic manner. There are experts who do this, often termed “sleuths”, that form the new field of forensic scientometrics.
Our current efforts
Support new tools & communities to detect fraud and data manipulation
Support training and awareness in identifying problematic research
Resources
Frequently Asked Questions
How do I detect fraud or data manipulation in research?
There are a set of open science integrity guides (created by experts at detecting these issues) designed to help available here: https://osf.io/2kdez/wiki/home/
What is fraud in academia?
Fraud in academia typically refers to the deliberate falsification, fabrication, or manipulation of research data, as well as plagiarism. These acts undermine the credibility of scientific findings and can seriously damage trust in scholarly communities
What are the consequences of fraud?
Consequences can include retraction of articles, damage to individual or institutional reputations, loss of funding, academic sanctions, and criminal or civil penalties in severe cases. More broadly, such misconduct undermines public confidence in science and can lead to harmful decisions based on false findings.
How does data manipulation happen?
Common examples include fabricating experimental results, falsifying data to fit hypotheses, cherry-picking data, or misrepresenting methods and findings. Plagiarism—presenting others’ work as one’s own—is also a form of academic fraud
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