Scientific Research and Communication — Avoiding Plagiarism

According to the UConn Code of Conduct, plagiarism would include, "failing to properly credit information, research or ideas to their rightful originators or representing such information, research or ideas as your own."

Below you will find a graphic that explains several types of plagiarism, notably:

• complete plagiarism
• paraphrasing plagiarism
• source-based plagiarism
• direct plagiarism
• auto plagiarism

If you have any questions about plagiarism, it is recommended that you make an appointment with the Writing Center at UConn, a librarian, or the Academic Achievement Center.

Plagiarism in the sciences can be different from plagiarism in the humanities in that other factors may be involved such as implying problematic data is valid.  The scientific process and scientific ethics are important to follow.  If you have any questions, it is important to consult with your professor, lab manager, or PI. The office of research can also answer questions.

Using, managing and citing research data ethically is everyone's responsibility, from researchers to college students writing papers. It is important to understand the consequences of scientific and data misconduct, and learn how to prevent them. 

The public and other researchers, publishers, and journalists watch for information about data misconduct, misuse, and falsification. The blog Retraction Watch is a well-known site tracking scientific misconduct. 

"Some research behaviors are so at odds with the core principles of science that they are treated very harshly by the scientific community and by institutions that oversee research. Anyone who engages in these behaviors is putting his or her scientific career at risk and is threatening the overall reputation of science and the health and welfare of the intended beneficiaries of research.

Collectively these actions have come to be known as scientific misconduct. A statement developed by the U.S. Office of Science and Technology Policy, which has been adopted by most research-funding agencies, defines misconduct as “fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results.

In addition to citing your reference sources when writing a paper, you must also cite any datasets you use. There are several resources to help you learn about data citation: