Close reading big data: The Echo Nest and the production of (rotten) music metadata

Abstract

Digital music distribution is increasingly powered by automated mechanisms that continuously capture, sort and analyze large amounts of Web-based data. This paper traces the historical development of music metadata management and its ties to the growing of the field of ‘big data’ knowledge production. In particular, it explores the data catching mechanisms enabled by the Spotify-owned company The Echo Nest, and provides a close reading of parts of the company’s collection and analysis of data regarding musicians. Doing so, it reveals evidence of the ways in which trivial, random, and unintentional data enters into the data steams that power today’s digital music distribution. The presence of such curious data needs to be understood as a central part of contemporary algorithmic knowledge production, and calls for a need to re-conceptualize both (digital) musical artifacts and (digital) musical expertize.

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