Whenever Possible, Image it!

Science is built on evidence, but too often our scientific results are reduced to bars and curves. With rising concerns about data integrity and reproducibility, we as scientists need to ask: how can we make our evidence more convincing, transparent and trustworthy?

One powerful answer is simple: whenever possible, image it. 

This should be a default mindset: always ask, how can I best image this process? An image, whether it is a microscopy picture, a gel, a spectrogram or even a carefully captured field photograph provides a level of directness that numbers alone cannot. It allows others to see the evidence for themselves, reducing reliance on abstracted summaries. Images bring us closer to the phenomenon being studied and make it easier to build confidence. Graphs and statistics remain essential for quantification but pairing them with images creates a more transparent and convincing story.

One could argue that images may be manipulated too. This is actually true. In fact, studies show that around 2% of scientists admit to falsifying or fabricating data at least once, and over 30% admit to questionable research practices (Fanelli, 2009). More recent large-scale analyses have revealed organized networks of fraudulent publications, some involving manipulated images and misleading data (Van Noorden, 2024). Even citation counts have been gamed through “sneaked references,” where false metadata is inserted to inflate impact (Gómez et al., 2023). Don't these trends make it clear that we must do more to strengthen trust among scientists?  So yes, while image fraud exists, it is often easier to detect through careful peer review than fabricated numbers or graphs. And importantly, images provide something that bar and line charts cannot: they reveal the actual dynamics of the process being studied. For instance, a molecular imaging study backed by raw visuals is inherently more convincing than one relying solely on abstracted curves or bars which can be too easily conjured.

An image communicates and anchors your work in reality. It provides context, reduces the risk of over-interpretation and invites others to verify and engage with your findings. In a time when public trust in science matters more than ever, showing the evidence is as important as interpreting it.

So next time you prepare your data, remember that curves and bars show trends, but images show reality.

Whenever possible, image it.

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References

Fanelli, D. (2009). How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data. PLoS ONE, 4(5), e5738. https://doi.org/10.1371/journal.pone.0005738

Van Noorden, R. (2024). Fraudulent research is everywhere, says new study. DW News. https://www.dw.com/en/fraudulent-research-is-everywhere-says-new-study/a-73533918

Gómez, A., et al. (2023). Sneaked references: Cooked reference metadata inflate citation counts. arXiv preprint. https://arxiv.org/abs/2310.02192