I was recently doing some research into the reproductive habits of crocodylians, looking for some possible information that might also apply to dinosaurs. While doing this, I was referred to a paper written by the the crocodile expert John Thorbjarnarson (who I will admit, I hadn’t actually heard of before), who tabulated reproductive data such as numbers of eggs, body mass, etc., on all of the living species of crocodylians. “Great”, I thought to myself, this is exactly the kind of data I as looking for. I started looking through the paper in a bit more detail, and saw that although he had already gathered all of the data that I was looking for, he had only published summaries of that data. No problem, I was thinking, the paper says to just contact the author for the original dataset. A little searching later turned up something a little more depressing than an email address: his obituary. He had tragically and unexpectedly died of malaria in 2010.
This brings me to the point of this post, about data archiving. John likely couldn’t have placed the data he collected in a long term, accessible archive like Dryad or Morphobank (and the many others that serve similar purposes) because the paper was published in 1996. However, the excuses I sometimes hear still that “the data is in the paper” and “if people want it, they can just ask me” don’t really apply in 2013. Of course, this is somewhat of a unique situation, but how many other scientists have been struck down by unforeseen circumstances? How many hours of work in compiling this data set (and many others) have been lost, even if it was something more mundane like a computer crash? The point is, you never know what the future may hold, but you can make sure that your scientific legacy persists well beyond yourself. You never know how far down the line (17 years in this case) someone might be looking to carry on your work.