The process of breaking up research is dangerous one, according to UH's Big Idea. Graphic by Miguel Tovar/University of Houston

Salami slicing, breaking a paper on a single study up into smaller “slices” and publishing them in more than one journal, is broadly discouraged and considered unethical. Why does the practice persist? What do PIs believe are the benefits of doing it?

Two problems

Breaking up research into smaller slices can have serious consequences for scientific integrity. Researchers, especially younger researchers, may get used to looking at data in smaller pieces and not as a whole. This is dangerous from an academic perspective as valuable conclusions, that could have been derived if the data were presented as a whole, are overlooked.

Further, salami slicing of data may do more harm than good to a researcher’s career over time because it significantly reduces their chances of publishing in high impact journals, thereby lessening the weight of their accrued body of work.

One reason salami slicing still persists, is that there is a veritable avalanche of papers vying for publication. And the number seems to be steadily increasing.

“The academic market became more competitive after the nation’s economic downturn, in 2008,” said Rodica Damian, UH associate professor of psychology. “We saw a lot of competition between those with Ph.D.s and those who were conducting postdoc research. Before, you needed a postdoc if you were in Biology, for instance – but you didn’t need one if you had a doctorate in Psychology. That is no longer the case.”

Another reason salami slicing might persist is that advisors may suggest to a graduate student that they write a series of simpler papers as opposed to a more complex paper consisting of multiple measurements. A researcher might get these “single-lens papers” published much more quickly than their multi-faceted counterparts, due to the amount of background research the journal’s editors need to do on the more complicated papers.

How to avoid self-plagiarism

Salami slicing is not necessarily self-plagiarism, but often the practice does feature a large amount of “text overlap,” according to Miguel Roig, Ph.D. on the website of the Office of Research Integrity for the U.S. Department of Health and Human Services. One example Roig gives is as follows:

“Several months ago, for example, we received a manuscript describing a controlled intervention in a birthing center. The authors sent the results on the mothers to us, and the results on the infants to another journal. The two outcomes would have more appropriately been reported together…The important point is that readers need to be made aware that the data being reported were collected in the context of a larger study.”

The Big Idea

An article published by the NIH suggests this rule of thumb: “If the ‘slice’ of the study in question tests a different hypothesis as opposed to the larger study or has a distinct methodology or populations being studied, then it is acceptable to publish it separately.”

However, when a colleague is trying to do a meta analysis, they need to know what your study actually measured. “One thing you can do to avoid salami slicing,” said Damian, “is to pre-register all the projects you’re planning to do from a specific data set. Then ask yourself, do they use different hypotheses, measures, literatures, etc.”

After all is said and done, are they substantively methodically different research papers? If so, they can be sent to different, separate journals.

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

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3 Houston innovators who made headlines in May 2025

Innovators to Know

Editor's note: Houston innovators are making waves this month with revolutionary VC funding, big steps towards humanoid robotics, and software that is impacting the agriculture sector. Here are three Houston innovators to know right now.

Zach Ellis, founder and partner of South Loop Ventures

Zach Ellis. Photo via LinkedIn

Zach Ellis Jr., founder and general partner of South Loop Ventures, says the firm wants to address the "billion-dollar blind spot" of inequitable distribution of venture capital to underrepresented founders of color. The Houston-based firm recently closed its debut fund for more than $21 million. Learn more.

Ty Audronis, CEO and founder of Tempest Droneworx

Ty Audronis, CEO and founder of Tempest Droneworx

Ty Audronis, center. Photo via LinkedIn.

Ty Audronis and his company, Tempest Droneworx, made a splash at SXSW Interactive 2025, winning the Best Speed Pitch award at the annual festival. The company is known for it flagship product, Harbinger, a software solution that agnostically gathers data at virtually any scale and presents that data in easy-to-understand visualizations using a video game engine. Audronis says his company won based on its merits and the impact it’s making and will make on the world, beginning with agriculture. Learn more.

Nicolaus Radford, CEO of Persona AI

Nicolaus Radford, founder and CEO of Nauticus RoboticsNicolaus Radford. Image via LinkedIn

Houston-based Persona AI and CEO Nicolaus Radford continue to make steps toward deploying a rugged humanoid robot, and with that comes the expansion of its operations at Houston's Ion. Radford and company will establish a state-of-the-art development center in the prominent corner suite on the first floor of the building, with the expansion slated to begin in June. “We chose the Ion because it’s more than just a building — it’s a thriving innovation ecosystem,” Radford says. Learn more.

Houston university to launch artificial intelligence major, one of first in nation

BS in AI

Rice University announced this month that it plans to introduce a Bachelor of Science in AI in the fall 2025 semester.

The new degree program will be part of the university's department of computer science in the George R. Brown School of Engineering and Computing and is one of only a few like it in the country. It aims to focus on "responsible and interdisciplinary approaches to AI," according to a news release from the university.

“We are in a moment of rapid transformation driven by AI, and Rice is committed to preparing students not just to participate in that future but to shape it responsibly,” Amy Dittmar, the Howard R. Hughes Provost and executive vice president for academic affairs, said in the release. “This new major builds on our strengths in computing and education and is a vital part of our broader vision to lead in ethical AI and deliver real-world solutions across health, sustainability and resilient communities.”

John Greiner, an assistant teaching professor of computer science in Rice's online Master of Computer Science program, will serve as the new program's director. Vicente Ordóñez-Román, an associate professor of computer science, was also instrumental in developing and approving the new major.

Until now, Rice students could study AI through elective courses and an advanced degree. The new bachelor's degree program opens up deeper learning opportunities to undergrads by blending traditional engineering and math requirements with other courses on ethics and philosophy as they relate to AI.

“With the major, we’re really setting out a curriculum that makes sense as a whole,” Greiner said in the release. “We are not simply taking a collection of courses that have been created already and putting a new wrapper around them. We’re actually creating a brand new curriculum. Most of the required courses are brand new courses designed for this major.”

Students in the program will also benefit from resources through Rice’s growing AI ecosystem, like the Ken Kennedy Institute, which focuses on AI solutions and ethical AI. The university also opened its new AI-focused "innovation factory," Rice Nexus, earlier this year.

“We have been building expertise in artificial intelligence,” Ordóñez-Román added in the release. “There are people working here on natural language processing, information retrieval systems for machine learning, more theoretical machine learning, quantum machine learning. We have a lot of expertise in these areas, and I think we’re trying to leverage that strength we’re building.”