+44 (0) 20 3828 1325 No 1 Croydon, CR0 0XTPromoting good practice and preventing misconduct

Academic Image Integrity


  • A paper describing the acceptable ways to manipulate a research image.

Cromey, D. W. (2010). Avoiding Twisted Pixels: Ethical Guidelines for the Appropriate Use and Manipulation of Scientific Digital Images. Science and Engineering Ethics. https://doi.org/10.1007/s11948-010-9201-y

  • Guidance from the seminal 2004 Journal of Cell Biology paper presents the problem of inappropriate image manipulation and gives general guidelines for the handling of digital image data in a simple/easily understandable way, with examples.

Rossner, M., & Yamada, K. M. (2009). What’s in a picture? The temptation of image manipulation. European Science Editinghttp://jcb.rupress.org/content/166/1/11.full

  • How to determine if a photo is fake.


  • How journals detect image manipulation in 2 parts.




Webinars and Video

  • HEADT Centre — Humboldt-Elsevier Advanced Data and Text Centre. This video introduces to the field of scholarly image manipulation and explains why it has become a serious concern in many scholarly fields: https://www.youtube.com/watch?v=CRSznah_xg0


 Further reading list

Recently the incidence of problematic digital academic research images in the published literature has been questioned. Hence, there have been efforts to establish whether there should be automation and specific tools to detect these manipulated images:

  • A paper looking at the prevalence of image duplication: Bik, E. M., Casadevall, A., & Fang, F. C. (2016). The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications. MBio. https://doi.org/10.1128/mbio.00809-16
  • A paper discussing the role of automatic detection of manipulated images in biomedical literature: Bucci, E. M. (2018). Automatic detection of image manipulations in the biomedical literature article. Cell Death and Disease. https://doi.org/10.1038/s41419-018-0430-3
  • Description of a tool designed to detect manipulated images: Koppers, L., Wormer, H., & Ickstadt, K. (2017). Towards a Systematic Screening Tool for Quality Assurance and Semiautomatic Fraud Detection for Images in the Life Sciences. Science and Engineering Ethics. https://doi.org/10.1007/s11948-016-9841-7

Last revised October 2019. 


Please note that this list of resources is not intended to be exhaustive and should not be seen as a substitute for advice from suitably qualified persons. UKRIO is not responsible for the content of external websites linked to from this page. If you would like to seek advice from UKRIO, information on our role and remit and on how to contact us is available here.

UKRIO would like to thank our Advisory Board and other volunteers for their help in putting this list together.

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