Keep Your Popular Name and Your Identity

I’m really glad I’m not one of the 46,155 John Smiths (in USA alone), or one of the tens of thousands of Liu Xiangs. In fact, I may be the only Kurtis Baute on the internet, at least for now.

But if I had such a common/popular name, then how could I possibly keep my publications straight? As it is, publications list authors by their names and university affiliations, but that is more than a little confusing if you have a common name, or if you change universities.

 

The idea behind ORCID is that everyone can get their own reference code, so that however common their name is, they can stay distinguished. It is like how species have common names (which get mixed up with one another all the time), but [hopefully] only one Latin name – without this organization, biology wouldn’t be able to operate.

It takes 30 seconds to get a reference code, and only a few minutes to fill out the rest of the profile. Even with my uncommon name, I think that this idea is so cool that I signed up in preparation for whenever I have an actual publication.

How Scientific Diagrams Evolve

Sometimes when I was doing my literature review for my thesis I would crawl down a rabbit hole, searching for the original source. Most often, this involved trying to chase down a particular statistic, hunting through review paper through the wrong primary research articles, and then ending up at one of three finish lines:

1)   I find the actual source with the statistic in a peer-reviewed journal article, which had been properly cited.

2)   I find the actual source with the statistic in a non-peer-reviewed article, book, or website post. It is interesting that people don’t cite the original source, possibly because citing a peer-reviewed article looks better (for those that aren’t looking very hard). Which leads to the final possible outcome:

3)   I find a total dead end, where the thing that was being cited simply didn’t exist. Someone makes up a figure, cites some author, and it gets published. Benefit of the doubt, some of these are very honest mistakes. Still, #fail.

I followed the evolution of a particular diagram back in time. Here are three scientific diagrams about the same thing  (a schematic representing the destruction of plant cell walls through pretreatment), published in three papers, in chronological order (ranging from 1980 to 2011):

plant cell wall pretreatment plant cell wall pretreatment plant cell wall pretreatment

I see an odd sort of beauty in how much the image improves. Like science itself, this image is adapted and sharpened as our understanding of it improves with time. People stand on the shoulders of giants, to draw ever-better diagrams of… plant pre-treatments.

Then this happens:

plant cell wall pretreatment

Credits: me, me, me?

Sure, it is a bit more of a change, and it wasn’t published in a scientific journal (actually, a University of Florida extension article). But it is interesting that although the author cited some of the papers that included the above diagrams, Tong decided to take all of the credit for the image. Is it plagiarism? Technically, yes.

What about the two examples below? They are even more different than the previous one was to the originals, and they don’t cite any previous sources.

plant cell wall pretreatment plant cell wall pretreatment

To me, watching how these images evolve over time stresses the importance of properly citing the original source. Firstly, it isn’t plagiarism, and secondly, by citing a good image, you’re less likely to end up with a poorly-drawn sad-face in your scientific article.

If nothing more, I see these sorts of diagrams as an interesting way to visualize the evolution of memes (as Richard Dawkins originally intended the word, not as the evolved meaning that the word has developed). Were these really distinctly evolved occurrences (like how bats and birds separately evolved the ability of flight), or are they just cheating mimics (like how some harmless snakes have evolved to look surprisingly like deadly venomous ones) ?