Models for Thinking: An Example of Why Data Sciences Increasingly Need the Humanities

Parsing such large-scale data sets – classifying genomic sequences, mapping forms of advertisement, observing online discussions, etc. – is a matter of organization: How do you make sense of, and classify, these clusters of information? The answer, often, is to configure them into abstract but coherent topics.