Therefore, let's see how to decide what to include:
What To Show
Essentially, you want to show the key points that make the implications of your work clear.
To my mind, this is a very well-designed graphical abstract that is very specific about what to show and clearly conveys the key takeaway of the paper.
As we discussed, you don’t simply visualize your written abstract—that quickly becomes overwhelming.
Instead, only prioritize the essentials needed to explain what the key takeaway of your work is.
Click to enlarge. Compare the graphical abstract on the right with the one on the left - the former is more convenient for the eye because it clearly outlines the observed changes. In other words, the authors prioritized the key features to show and went through the hardship of omitting everything else. For example, the “Tubule” on the left is information that is not needed and only adds blur. But of course, for some papers this will always be easier than for others.
How To Do It
It’s often advised to summarize the main message of your work in one sentence and then try to visualize it.
You might disagree but I think this is misleading.
This one sentence makes you focus too narrowly - it doesn’t yield enough content and therefore often leads you to adding too many “details” later on, which eventually overcrowds the graphical abstract.
Turning the draft on the left into a visually clear graphical abstract is challenging—there is too much information, all of which seems relevant.
This is why I would approach it differently:
First implication
Second key points
Third design
Start by identifying what the key implication of your work is.
In other words: What novel insight would make it into a textbook? What could your method achieve once optimized? What does the drug you invented actually do?
This is what should remain in your reader’s mind in the end.
For you, it sets the stage and provides orientation for what to include and what you need to highlight visually later.
This graphical abstract represents the key idea very well: the incorporation of non-canonical amino acids. The key components include the design of the aaRS operon, tRNA operons, and O-mRNA, as well as their integration. This makes sure they understand what the work is about, what it contributed to the field, and that you stay concise but still have enough elements to fill your graphical abstract.
But instead of designing from there, you then think about the key points that enable your reader to grasp this advance.
In other words, ask yourself which string of key points would give someone else the best understanding of the key implication you identified above.
Tips For Prioritization
Of course, we are talking about key points, not every interesting aspect of your work—that’s why prioritization is so important.
Pro tip: Yes, this can be especially difficult when you are deeply immersed in your own research. However, try not to think about what you did.
Instead, create for someone writing a review three years from now, thus only caring about the combined final outcome of your work.
When we think of our own work, we are easily drawn to our memories of our experiments and the thought processes behind our investigations. However, this often distracts us when it comes to focusing on the implications of our work.
If you have changed fields or are publishing outside your usual area, rethink your prioritization based on the audience that will read your work.
Academics often care most about novelty.
Biotechnologists may be more attracted by methodological innovations.
Medical professionals or those in translational research will prefer clinical relevance.
The list continues … when you write perspectives or opinion pieces, public health implications or broader societal impact may be most relevant.
Methods Or Not?
Finally, a common hurdle is deciding whether you should include methods... It's not mandatory but can certainly make sense:
In this example, including the methods made sense because experiments with monkeys are comparatively rare (valuable to explain), easy to visualize, and the authors had a fitting layout of how to present the neuronal aspects.
However, it is highly advisable if your methods add to the significance of your work, i.e., if they are new, optimized, or essential for understanding the results.
A few examples where including methods makes sense:
You use HPLC to analyze immune cells (instead of flow cytometry).
You analyze environmental samples with HPLC to identify pollutants.
You push conventional light microscopy to nanometer-scale resolution.
Other than that, if you already use a flow scheme, it can be a nice addition -but only if it doesn’t overcrowd your design.
This can happen very quickly, especially if you include many standard methods (such as PCR or SDS-PAGE) that do not add meaningful information to the message.
How We Feel Today
Yes, also this an actual graphical abstract – you can read more here.
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