THE ROLE OF BREAKDOWN IN IMAGINING BIG DATA: IMPEDIMENT TO INSIGHT TO INNOVATION

Abstract

As the era of “big data” unfolds, researchers are increasingly engaging with large, complex data sets distributed across various networked technologies. The vast and distributed nature of these data sets makes it difficult to envision them in their entirety and often leads to encounters with breakdown – points at which progress is stopped due to a material obstacle. Based on an ethnographic study of data-intensive research in an academic setting, this paper explores the role of breakdown in the process of working with big data. We suggest that encounters with breakdown reveal the materiality of digital data and allow researchers to more clearly imagine its vast content and structure. Often dismissed as impediments that slow or derail a typical process of scientific inquiry, we argue that encounters with breakdown are underappreciated resources that represent essential sites of knowledge production for big data analysis. In focusing on breakdown, we are able to trace the iterative process of envisioning the data, generating insights into the data, translating insights into strategies for managing the data, and encoding those strategies into communication with the data. Thought of in this way, productive encounters with breakdown have significant design implications, in that the data science community may benefit from tools and platforms that facilitate communication between data and researcher by more explicitly calling attention to points of breakdown.