Nevertheless, any manipulation that violates these guidelines is a misrepresentation of the original data and is a form of misconduct.

That is, creating a result is worse than making weak data look better. There are different degrees of severity of a manipulation, depending on whether the alteration deliberately changes the interpretation of the data. Here we present some general guidelines for the proper handling of digital image data and provide some specific examples to illustrate pitfalls and inappropriate practices. To avoid such a situation, it is important to understand where the ethical lines are drawn between acceptable and unacceptable image adjustment. government: “Research misconduct is defined as fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results.” For example, showing a figure in which part of the image was either selectively altered or reconstructed to show something that did not exist originally (for example, adding or modifying a band in a polyacrylamide gel image) can represent falsification or fabrication.īeing accused of misconduct initiates a painful process that can disrupt one's research and career. In the current definition provided by the U.S. Consequently, to protect the integrity of research, the scientific community takes strong action against perceived scientific misconduct. Skilled editorial staff can spot such manipulations using features in the imaging software, so manipulation is also a risky proposition. Many such manipulations, however, constitute inappropriate changes to your original data, and making such changes can be classified as scientific misconduct.

It is now very simple, and thus tempting, to adjust or modify digital image files. In the days before imaging software became so widely available, making adjustments to image data in the darkroom required considerable effort and/or expertise.

In an image manipulation program