Difference between revisions of "Theme:20f32f16-72a1-46f0-b9a6-24fac05b0937"
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For those reviewing papers, a free open source program, called InspectJ, is available on GitHub to identify cloning, stitching, patching and erased objects within an image. An advanced version also provides histogram equalization and gamma correction for improved image inspections (both available at: https://github.com/ZMBH-Imaging-Facility/InspectJ, accessed on 24-04-2020) | For those reviewing papers, a free open source program, called InspectJ, is available on GitHub to identify cloning, stitching, patching and erased objects within an image. An advanced version also provides histogram equalization and gamma correction for improved image inspections (both available at: https://github.com/ZMBH-Imaging-Facility/InspectJ, accessed on 24-04-2020) | ||
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Revision as of 12:28, 4 August 2020
ThemesImage Integrity
What is this about?
Why is this important?
Images often serve as primary data (e.g. cell biology). In other instances, they are key in making an article attractive to read or serve comprehensive purposes. Accordingly, images are often included in article abstracts. The information they carry is thus a vital part of research and should remain identical to what is observed in the experiment (Rossner & Yamada 2004).
Mike Rossner, Kenneth M. Yamada; What's in a picture? The temptation of image manipulation . J Cell Biol 5 July 2004; 166 (1): 11–15. doi: https://doi-org.vu-nl.idm.oclc.org/10.1083/jcb.200406019For whom is this important?
What are the best practices?
The KU Leuven has a dedicated webpage on image integrity. They identified some of the most important sources and tools regarding the subject (available at: https://www.kuleuven.be/english/research/integrity/practices/image-processing, accessed on 24-04-2020). As their page is very brief, a more elaborate description of what it contains, and additional sources, follow below.
Rossner & Yamada (2004) wrote a prominent article arguing for a standard for image integrity. Both working as editor for The Journals of Cell Biology, they noticed the discrepancy and wide range of guidelines journals gave to their authors (if any). To have a comprehensive overview, they propagate their own guidelines of the Journal of Cell biology. They write that, for every aspect of the guideline the main question is: “Is the image that results from this adjustment still an accurate representation of the original data?” (Rossner & Yamada 2004, p. 5). Whenever the answer is ‘no’, researchers should provide a detailed description of the adjustments, its purpose and the original image on request. If not, their actions might be regarded as misconduct.
A step-by-step translation of the abovementioned guideline is available at the website of American Journal Experts (at: https://www.aje.com/en/arc/avoiding-image-fraud-7-rules-editing-images/, accessed on 24-04-2020) and at the KU Leuven webpage. A similar guideline, and additional editorials on the subject, are given by the journal Nature on their editorial policies page (available at: https://www.nature.com/nature-research/editorial-policies/image-integrity, accessed on 24-04-2020).
The Center for Ethics and Values in the Sciences, of the university of Alabama at Birmingham, created a website for both students and researchers with much material regarding image integrity (available at: https://ori.hhs.gov/education/products/RIandImages/default.html, accessed on 24-04-2020). They provide guidelines with more in dept explanations and illustration videos, but also educational material such as case studies, discussion hand outs and a quiz.
The office of research integrity provides a tutorial on how to use ‘action sets’ in photoshop (available at: https://ori.hhs.gov/actions, accessed on 24-04-2020). They actions sets allow you to document the changes you make to the image and ‘slide’ (i.e. going back and forward) between all the steps you made. The process of the image you manipulated will hereby be completely transparent if you provide the ‘action set’ combine with a copy of the original image.
For those reviewing papers, a free open source program, called InspectJ, is available on GitHub to identify cloning, stitching, patching and erased objects within an image. An advanced version also provides histogram equalization and gamma correction for improved image inspections (both available at: https://github.com/ZMBH-Imaging-Facility/InspectJ, accessed on 24-04-2020)Iris Lechner, Natalie Evans, Fenneke Blom, Philipp Hoevel, Andrijana Perković Paloš, Tom Lindemann contributed to this theme. Latest contribution was Oct 22, 2021
