STM STEC Working Group on Image Alterations and Duplications
Please find in the below link the recording dated 14/09/21
Webinar on STM's draft recommendations for handling image integrity issues
'STM Recommendations for handling image integrity issues' - open for comments until October 31st (https://osf.io/xp58v/)
In scholarly publishing we encounter image alterations as well as duplications. Whatever the reason is behind the submission of altered and/or duplicated images to a journal, they should be identified early in the article evaluation process, so journals can take appropriate action prior to publication and in a best case scenario, before peer review. Opposite to text plagiarism, which usually results in the violation of the research process, image alteration and/or duplication can be much more damaging, as it corrupts actual research results, wastes research money on invalid leads, undermines society’s trust in research, and can even endanger the society in which those “results” are used.
Automatic detection in text plagiarism is nowadays commonplace, and standard tools are widely adopted by scholarly publishers, while detection of image alteration and/or duplication is not. Tools that can assist journals in the detection of image alteration and/or duplication are now being developed by both academic research groups and commercial vendors.
The STM Standards and Technology Committee (STEC) has appointed a working group to answer questions around automatic image alteration and/or duplication detection. It will address topics like the minimal requirements for such tools, the current quality of them, how their quality can be measured, and how these tools can be widely, consistently, and effectively applied by scholarly publishers. In preparation of this focus on tools, it will also look at a standard classification of types and severity of image-related issues and propose guidelines on what types of image alteration is allowable under what conditions.
The members of this working group are:
- Sowmya Swaminathan, Springer Nature
- Jon Slinn, Wiley
- Sarah Robbie, Taylor & Francis
- Teodoro Pulvirenti, American Chemical Society
- Bernd Pulverer, EMBO Press
- Jacob Kendall-Taylor, JAMA
- Catriona Fennel, Elsevier
- SJ MacRae, Aries System
- Tim Spencer, Rockefeller University Press
- Joris van Rossum, STM
- IJsbrand Jan Aalbersberg (chair), STM STEC and Elsevier
The Working Group has been developing best-practice recommendations that outline a structured approach to support editors and others applying image integrity screening as part of pre-publication quality control checks or post-publication investigation of image and data integrity issues at scholarly journals, books, preprint servers, or data repositories. It provides principles and a three-tier classification for different types of image and data aberrations commonly detected in image integrity screens of figures in research papers and for a consideration of impact on the scholarly study; it also recommends actions journal editors may take to protect the scholarly record. With these recommendations, the STM Working Group aims to contribute a consistent, structured and efficient framework for handling image integrity issues both within and between journals and publishers. The framework should support editors in safeguarding research integrity and fortifying the scientific process for the benefit of the scientific community.
The recommendations are open for comments until October 31st. The final recommendations, in which we will attempt to process all suggestions and recommendation, will be presented at the STM Innovations Seminar on December 7th.
To read the recommendations and add your comments, please visit https://osf.io/xp58v/
- Bik, E.M., Fang, F.C., Kullas, A.L., Davis, R.J., Casadevall, A. (2018), Analysis and correction of inappropriate image duplication: The molecular and cellular biology experience, Molecular and Cellular Biology 38 (20), e00309
- Rossner, M. (2002), Figure manipulation: assessing what is acceptable, The Journal of Cell Biology 158 (7), 1151
- Williams, C.L., Casadevall, A., Jackson, S. (2019), Figure errors, sloppy science, and fraud: keeping eyes on your data, The Journal of Clinical Investigation 129 (5), 1805-1807