As we abstract higher and higher we are finding insights through patterns / themes and learning by separating concerns, conversely as we make our way down to the data points, we are understanding the precision and nuance in our data through learning by example.

This is a fantastic post about data visualization design and about the usefulness of being able to traverse up and down the various level of abstraction naturally present in data. This feels intuitive when it comes to zooming in and out of Google Maps, but there are very explicit design features that enable the experience to be a good one.


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