YODA

Prelude: Scientist in a data labyrinth As experimental neuroscientist in training, I often find myself caught between two worlds: the messy, exploratory world of data analysis where I try to make sense of the experimental data, often relying on a trial-and-error strategy, and the aspired structured, reproducible world of scientific publication where hopefully every figure will be exactly reproducible. Between these worlds lies a labyrinth of processing pipelines, half-written scripts, and the ever-present risk of breaking the working analysis while trying to improve it. The wandering in the labyrinth is rarely straight-forward – one is expected to hit many dead ends and discover other interesting distractions before finding the actual treasure – the key results that hopefully lead to a scientific publication or other forms of consolidated knowledge piece. I try to illustrate this metaphoric labyrinth that is my non-metaphoric reality in a diagram: ...