Ben Schneiderman’s 8 Golden Rules of Datascience

This popped up in my twitter feed today – it’s a photograph of a slide from a talk given by Ben Schneiderman. I’m not sure I’d call them golden rules per se, but they are definitely a very decent framework to follow:

Preparation

  • Choose actionable problems and appropriate theories
  • Consult domain experts and generalists

Exploration

  • Examine data in isolation and contextually
  • Keep cleaning and add related data
  • Apply visualization and statistics: patterns, clusters, gaps, outliers, missing and uncertain data

Decision

  • Evaluate your efficacy, refine your theory
  • Take responsibility, own your failures
  • World is complex, proceed with humility.

Professor Schneiderman’s home page is here. The link to the tweet I picked all this up from is here via Kirk Borne and Seth Grimes

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