What do you fear most?
Ask a normal person and they might say: the dark, a clown attack, or (my personal) spiders with wings. (As a humorous aside, I was once having a philosophical discussion with a friend about the afterlife, when I remembered being told that people are born with only one fear, that of dying. I thought it apropos, and began: “I’m told that people are born with only one fear…”. Before I could finish my thought he suddenly exclaimed “Bees! It’s got to be bees!” That still makes me laugh.). Ask a scientist his greatest fear however, and most likely they will talk about not receiving credit for their work. Terrifying!
Joke’s aside, this is a legitimate concern, and with the rise of ‘open data’, publicly available data and methodologies, discourse surrounding the regulations that ensure accreditation has resurfaced. These are undoubtedly legitimate fears, and we must make sure things are kosher as we move into the future. However in this blog I would like to raise similar fears stemming from the opposite end of the credit debate that are likely to exacerbate with more and more people sharing data: namely, people receiving credit for things they would rather not take credit for.
Last year, my lab lent some data to be included in a nationwide analysis investigating the effects of climate change on amphibian communities in the US. The researchers were gracious and assured us that we would be credited as co-authors for our trouble. A year goes by, nothing more has been heard about this paper until one day, out of the blue, a final draught arrives in our inboxes. The lead investigator has sent it to us as more of a courtesy, to check for any last minor errors before sending it out for publication. But for all intents and purposes, it is complete. Excited and surprised, we read over the paper… oh dear. Grade-A nonsense. From start to finish. Wacky methods, dubious conclusions, and worst of all, our names proudly at the top. Immediately we replied voicing our concerns, as politely as we could. But our plea fell on deaf ears, the PI was not going to budge; he had fallen in love with his analysis and was all but ready to submit the thing. Being a young naïve graduate student I wasn’t particularly worried, I just assumed the paper would never make it past review. My advisor was not as confident. The ‘climate change’ hook, combined with some of the big names listed as co-authors, would give it a really strong chance she argued. Scandalous!
In the end our consciences gave way and we asked for our names to be removed from the paper. But what if we hadn’t been sent the final edit as a courtesy? What if the first we heard about it was from reading the paper in print? Nor is this a benign issue. Imagine I borrow some of Stephen Hawking’s data, and then credit it him as a co-author. Publishers and readers alike are going to look extremely favorably on that paper, not knowing the minimal extent of the professor’s contribution.
With credit we walk a tightrope; leaning too far in either direction can prove disastrous. This balancing act is by no means new, but in the age of ‘open data’, we will likely have to walk the line far more often.