So here’s an interesting (to me) exercise I did in self-data-collection-and-analysis. I analyzed my publications from grad school and before (at OHSU), from my post-doc (at UW), and from my current scientist position (at PNNL). I determined the number of times each article had been cited by another publication per year, which is the Impact Factor of the article and plotted that versus the Impact Factor for the journal that the article was published in, which is the same idea only averaged over all the articles published in that journal. Here’s the plot I came up with:
This is interesting because it seems to show a couple trends. First is that it looks like all my publications from post-doc and my current position outdo the journal impact factor by 3.8x and 2.4x, respectively. That’s a good thing I think. The other is that my grad school publications do worse than the journal’s IF. This could be because of their age since papers hit a peak of ‘relevance’ when they are cited most, then taper off when they are supplanted by more current references. Not sure.
The one outlier is a paper that I worked on to analyze the genome of Oryza sativa, rice. It has a pretty large citation record, but I was interested to see what the trends would look like without it in the picture. Removing that point I got:
Now this seems to show that my current work is significantly outperforming my post-doc and grad school work by quite a bit. Again, not a bad thing I think. Also, in general I’m publishing in lower impact journals, but since I’m outperforming their impact factors maybe I should be shooting higher. I’ll send these plots along with my next submission to Nature. I think the editors will see it my way.