Data Carpentry by David Mimno.
From the post:
The New York Times has an article titled For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights. Mostly I really like it. The fact that raw data is rarely usable for analysis without significant work is a point I try hard to make with my students. I told them “do not underestimate the difficulty of data preparation”. When they turned in their projects, many of them reported that they had underestimated the difficulty of data preparation. Recognizing this as a hard problem is great.
What I’m less thrilled about is calling this “janitor work”. For one thing, it’s not particularly respectful of custodians, whose work I really appreciate. But it also mischaracterizes what this type of work is about. I’d like to propose a different analogy that I think fits a lot better: data carpentry.
Note: data carpentry seems to already be a thing
I’m not convinced that “carpentry” is the best prestige target.
The first mention of carpenters on a sorted version of the Nordic Scores (Colorado Adoption Project: Resources for Researchers. Institute for Behavioral Genetics, University of Colorado Boulder) is at 147.*
I would go for data scientist since mercenary isn’t listed as an occupation. 😉
The usual cautions apply. Prestige is as difficult or perhaps more so to measure than any other social construct. The data is from 1989 and so may not reflect “current” prestige rankings.
*(I have removed the classes and sorted by prestige score, to create Sorted Nordic Scores.)