Baby steps for the Open-Curious | Practical Data Management for Bug Counters

"There are a lot of good reasons to practice Open Science. Reproduciblity. The ability of science to meaningfully build on itself, rather than act as isolated case studies.3 To democratize access to information. To allow the public to see the details of the scientific process so they don’t see academia as a group of insular nerds. These are a good things, and I’m sold. Most scientists will agree. But. One of the things us starry-eyed idealists in the Open Science community are really bad at is acknowledging that there are a lot of disincentives to open practice. Below are some disincentives I’ve personally heard articulated when I’ve been pontificating on Open Science:

Share your data? But I’d have to change how I set it up, that’ll mess with my system/people may scoop me/the data is mine dangit/I won’t get credit if someone uses it

Share your code? Version control? Um, no, that’s a terrible idea. Besides, Git is an obtuse, practically impenetrable rabbit hole of brospeak4/Also people will scoop me

Preprints? Are you insane? The journal I want to publish in will not publish things that are previously published, I know a guy whose paper got rejected because it was based on his dissertation.

Publish in an open access journal? Aren’t those predatory?/in my field, people only publish in OA if they’re desperate/ Um, PLOS is so expensive that we can really only afford to publish there on special occasions.

Practice open science, in general? I wouldn’t know where to start/I don’t have time/I’m doing fine without it/ Be quiet Christie, you’re annoying.

With all these disincentives in play, it’s really hard for the open-curious5 to figure out how to break in. Especially if it’s presented in an all-or-nothing monolith. Especially if the open science community receives movements towards open practice with a derisive “Yeah, but why aren’t you doing more?” ..."