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Understanding Data

Publication information:

Lev Manovich, "Data," in Critical Terms in Futures Studies, ed. Paul Heike, Palgrave, 2019.

From the article:

"How is a data representa0on of some phenomenon or process different from other kinds of cultural representa0ons humans used until now, be they representational paintings, literary narratives, historical accounts, or hand-drawn maps? First, a data representation is modular, i.e., it consists of separate elements: objects and their features. Secondly, the features
are encoded in such a way that we calculate on them. This means that the features can take a number of forms—integers, floating-point numbers, categories represented as integers or text labels, spatial coordinates, etc.—but not just any form. And only one format can be used for each feature.

In other words, today “data” is not just any arbitrary collec0on of items existing in some medium such as paper. In a computa0onal environment, “data” is something a computer can
read, transform, and analyze. This imposes fundamental constraints on how we represent anything.

What is chosen as objects, what features are added, and how these features are encoded—these three decisions are equally important for represen0ng phenomena as data and,
consequently, making them computable, manageable, knowable, and shareable through data science techniques.

Article  2019