Institutions typically treat research integrity violations as black and white, right or wrong. The result is that the wide range of grayscale nuances that separate accident, carelessness, and bad practice from deliberate fraud and malpractice often get lost. This lecture looks at how to quantify the grayscale range in three kinds of research integrity violations: plagiarism, data falsification, and image manipulation.
Quantification works best with plagiarism, because the essential one-to-one matching algorithms are well known and established tools for detecting when matches exist. Questions remain, however, of how many matching words of what kind in what location in which discipline constitute reasonable suspicion of fraudulent intent. Different disciplines take different perspectives on quantity and location. Quantification is harder with data falsification, because the original data are often not available, and because experimental replication remains surprisingly difficult. The same is true with image manipulation, where tools exist for detecting certain kinds of manipulations, but where the tools are also easily defeated.
This lecture looks at how to prevent violations of research integrity from a pragmatic viewpoint, and at what steps can institutions and publishers take to discourage problems beyond the usual ethical admonitions. There are no simple answers, but two measures can help: the systematic use of detection tools and requiring original data and images. These alone do not suffice, but they represent a start.
The scholarly community needs a better awareness of the complexity of research integrity decisions. Only an open and wide-spread international discussion can bring about a consensus on where the boundary lines are and when grayscale problems shade into black. One goal of this work is to move that discussion forward.
Table of Contents
State of the Art
Quantifying Data Falsification
Quantifying Image Manipulation
Applying the Metrics
About the Author(s)Michael Seadle
, Humboldt-Universitat zu Berlin
Michael Seadle is a professor at Humboldt-Universitat zu Berlin, and is the chair of the Commission on Research Malpractice. His experience with research integrity issues builds in part on over 20 years of experience as a journal editor, where he confronted plagiarism and other research integrity issues. As dean he also dealt with such issues at the bachelor's and master's level. When Elsevier approached him to fund a research project, he suggested research integrity. This led to the establishment of the HEADT Centre (Humboldt-Elsevier Advanced Data and Text Centre), whose mission is in part to investigate research integrity issues.
His background blends multiple fields. Early in his university career Seadle studied chemistry, but discovered that he did not like the lab work and spent his time working on computing issues. After studying in Vienna, he switched to history, and completed a doctorate in that discipline at the University of Chicago under the supervision of William H. McNeill. He returned then to computing, and worked for years in industry before making his way back to the academic world at Cornell and Michigan State University. In 2006 he was called to Berlin to strengthen the research reputation of the Berlin School of Library and Information Science (Institut fur Bibliotheks-und Informationswissenschaft at Humboldt-Universitat zu Berlin). In Berlin he has served as chair of the international iSchools group, and has received multiple grants from the German Research Society (Deutsche Forschungsgemeinschaft), particularly in the area of longterm digital archiving. At the university he has been director of the School, dean of the Fakultat, and chair of the University Council.