Re:Stencila: An open source office suite for reproducible re...
by a_136_chiffa on Monday July 16, 2018 @10:26AM
(#17541461)
The issue is not to repeat the experiments, but rather to avoid putting the logs in the wheels of people who want to re-analyze your existing data (including yourself a couple of years later) and avoid losing thousands of working hours doing forensic data analysis to point out shitty science. Keith's Baggerly 2010 talk on the hoops he had to jump through to get to Anil Potti (https://en.wikipedia.org/wiki/Anil_Potti) is a great demo of the application case: https://youtu.be/7gYIs7uYbMo.
And as for "doing real science" vs. trying to make it more reproducible, there is an excellent analogy with "doing real programming" (aka adding features) vs. refactoring and architectural adjustments. Telling that you consider the second as a waste of time tells more about yourself than about the subject.
The "reproducibility" mantra is at odds with a lot of real world science and serious computing. You don't/can't in general reproduce the sort of physics experiments and large-scale calculations with which I'm most familiar the way people are suggesting, and software engineering can't address bad science or lack of information. Revision control and "notebook" interfaces seem to have become the equivalent of waving XML metadata at any problem from the days when e-science was preventing useful work and research. Experience from a non-trivial research record and some decades doing and supporting research computing will be ignored, though.