Let us FIGURE it out: Why do scientists still make “bad” figures?

In an era of high-resolution displays, powerful design software, and automated plotting tools, one would think that scientific figures would be clearer than ever. Yet, despite numerous editorials, guidelines, and workshops dedicated to improving figure design, poorly constructed figures remain a persistent issue. Editors and experienced researchers have repeatedly highlighted key pitfalls such as cluttered layouts, inconsistent formatting, poor color choices, and misleading visuals. (1−8) Yet, the aforementioned graphical shortcomings continue to plague even high-impact journals. Why? The problem is not a lack of technology; it is a combination of poor design habits, rushed deadlines, and a tendency to treat figures as mere “data dumps” rather than as essential storytelling tools. Many people process information more effectively through visuals, naturally associating concepts easily when presented graphically. A well-crafted figure serves as a narrative within the larger story, making complex ideas more accessible. Unfortunately, visual storytelling often takes a backseat in scientific communication. Scientists are trained to analyze and interpret data, but many default to software-generated plots without considering accessibility or how their figures will be perceived by readers outside their immediate field. Without thoughtful design, figures lose their power to enhance understanding, ultimately limiting the significance of the research itself. In this editorial, we examine the challenges that, in our view, hamper scientific figure design and discuss how thoughtful refinements driven by feedback, iteration, and design principles can enhance clarity and impact visual communication.