When writing a PhD thesis or an academic paper, you tend to be limited in how you can present results by the physical paper size, e.g. A4 for a thesis and often much tighter when targeting journals or conference proceedings.

This seems needlessly restrictive in this day and age, but perhaps that's a different discussion about the whole academic publishing machinery and its implications for good research.

My question is: how do you approach presenting data in a way that doesn't lose detail and impact, but fits in 15 x 25 cm (if you're lucky)?

I'll use an example to illustrate - after one set of experiments I have a plot that looks like this:

grid of plots with highlighted lines

This plot could be really useful in drawing out lots of conclusions and further questions. As it is, it only covers a sample of the actual results, but shows important trends and differences.

I've had a few ideas about how I might present this. I could:

  • Make an interactive visualisation available online and refer to it in the printed paper - printing just a small sample there but referring to the full results in the commentary.
  • Summarise the findings using tabulated numbers and perhaps just present one example (corresponding to one column of the image above).
  • Just squeeze it in somehow to give a "big picture" and then explain and point to full results elsewhere.

I wondered if this is a common problem and what good practice exists out there.

  • 5
    You need to further reduce your data. Make a concise model that describes it all. Nov 5, 2020 at 9:59
  • 5
    You could put detail like this in a supplement. Nov 5, 2020 at 10:00
  • Regarding "needlessly restrictive": there is a finite supply of reviewers and time that those reviewers have.
    – user116675
    Nov 5, 2020 at 10:21
  • 5
    If you find the paper size too restrictive, that usually means you should spend more time on creating a better visualization of the data.
    – user9482
    Nov 5, 2020 at 11:37
  • 2
    @JonCuster yes, I was thinking pretty much the same thing. Basically the capacity of the human brain to absorb and process information is a much narrower bottleneck than the paper size.
    – Dan Romik
    Nov 5, 2020 at 22:45

2 Answers 2


Many journals nowadays allow you to create ‘online appendix’ which is usually not subject to page limit. Hence you might want to just put it there if possible.

I would recommend you to just report aggregate figures in main body. No matter how many results you have there will usually be some way of aggregating them. Sure some information is lost in such process but if you will include more than 50 pages of graphs you will likely just deter potential readers, so it is often worthwhile trade off.


What do you want your readers to take from your 66 plots? You did alot of work? Great so has everyone else.

You say your plots could be used to "be really useful in drawing out lots of conclusions and further questions". Well that is your job as the author to do in the first place. As a reader if i see that in a paper, then that tells me you haven't analyzed your data and are leaving it to me to understand what your data shows.

Instead i'd either pick a couple of the most interesting/relevant plots to show, or work out how to combine all the plots in to one bigger plot.

I expect a lot of the trends could be presented more concisely simply as text. Are all 66 plots/parameters equally interesting to a reader? Probably not, they might be interesting to someone who is looking to repeat your work in which case i'd just put that data in a table (and put that in the supplementary material).

  • 3
    +1, giant tables of all this data in an appendix or online, BUT NOT IN THE MAIN TEXT! Sorry, had to get that off my chest. It's just unreadable to have a 5-page table of numbers when 3 numbers seem to matter. Please don't do a giant table in your conference talk either! Offer the full data up online, tabulate what's really important in an appendix in the paper, and plot something that's legible and concise in the main text.
    – Bill Barth
    Nov 5, 2020 at 16:00

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