The process of making data portable also screens off sensitive, local, or highly contextual modes of understanding. In transforming understanding into data, we typically eliminate or reduce evaluative methods that require significant experience or discretionary judgment in favor of methods that are highly repeatable and mechanical.

So here is the first principle of data: collecting data involves a trade-off. We gain portability and aggregability at the price of context-sensitivity and nuance. What’s missing from data? Data is designed to be usable and comprehensible by very different people from very different contexts and backgrounds. So data collection procedures tend to... See more

Not all kinds of knowledge, and not all kinds of understanding, can count as information and as data. Historian of quantification Theodore Porter describes “information” as a kind of “communication with people who are unknown to one another, and who thus have no personal basis for shared understanding.” In other words, “information” has been... See more

there are so many important factors that are far harder to measure: happiness, community, tradition, beauty, comfort, and all the oddities that go into “quality of life.”