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This chapter traces the cloud of digital data back to the data centers that store them. For security reasons, a number of data centers are repurposed Cold War military bunkers, suggesting that a military rationale for a bunker, to defend an area of territory, has re-entered the realm of data. By dividing networks into logical zones of inside and outside, these security infrastructures raise the specter of attack from those that might be ‘outside’ to network society, such as Chinese hackers or Iranian cyberwarfare specialists. By revisiting Paul Virilio’s Bunker Archaeology, this chapter further suggests that the specter of a disaster that the cloud continually raises also carries within it a temporality of a user’s imagined death. This temporality animates a recent series of digital preservation projects, such as the ‘Digital Genome’ time capsule, intended to survive the “death of the digital.”

This chapter takes a geographical perspective on a medical biotechnology known as Wireless Body Area Network (WBAN). WBANs generate, transmit, store, and retrieve information about the biological functioning of patients from any location, allowing doctors to watch their symptoms from computer screens at different locations. The chapter asks what happens to the body when millions of data points are collected from it, and are stored in data center facilities that are increasingly altering urban and rural landscapes. The chapter builds from an ontology based in object relations (e.g. bodies and material, digital information) to propose a different ontology based in extensibility. The political project is potentially vast. When data centers and the landscapes in which they are situated become pieces of the body itself, they must be given greater care and protection by the law.

This chapter examines data centers, statisticians, data managers, and collaborators within cooperative oncology groups who took over the management of clinical trials and their results. It also discusses the applications of statistics in clinical cancer trials, the design of multicenter trials, the stratification of treatment randomization by institutions, the advent of computerized techniques, and the introduction of organizational innovations by statisticians.

This chapter examines how recent depictions of data-center visibility function both as a mode of claiming corporate territory and as an obfuscation of the less picturesque dimensions of cloud infrastructure. Analyzing media infrastructure industries, such as the companies that run cloud systems, presents particular challenges for researchers. The structural convergence and functional heterogeneity of media make it difficult to apply some of the tried and true concepts in media and communication studies, such as the distinction between public and private. Using the Swedish data center as an example, the chapter then deciphers the backend of Internet architecture and data-trafficking policies, and highlights the importance of a relational perspective in understanding data centers as dynamic infrastructure nodes.

The chapter attempts to situate labor’s place in social media. It turns to aspects of the political economy of social media which are often obscured behind the debates about fake news, privacy and data protection: the infrastructure of social media. Hidden in these infrastructures, we find workers such as content moderators who scan social media platforms for any form of illicit content or “raters” – human workers whose job is to improve search algorithms. Content moderation labor proves to be especially hard emotional labor: workers regularly confront the darker sides of web culture and the emotional aspect of such labor is very hard for many to endure. Scanning up to 6,000 pictures or 1,000 videos every day, many of which contain brutal violence or hate speech, leaves many workers with emotional scars. Exploring the labor behind code, data centers, and content moderation, Chapter IV sheds light on the different and often hidden forms of labor that are crucial to both social media and other sectors of the digital economy.

The chapter addresses the cost of climate-related events by examining the impact on agricultural prices. The main goal is to examine the sensitivity of agricultural prices and output to local and nonlocal weather fluctuations over a large span of time in the United States prior to 1932, when markets were relatively unfettered by farm programs. The study assembles a thirty-seven-year panel of state data from the U.S. Department of Agriculture (USDA) for cotton, corn, wheat, and hay and from the National Climatic Data Center for temperature and precipitation, including the Palmer Drought Severity Index (PDSI). Changes in temperature and precipitation, and weather disasters like droughts, floods, heat waves, and blizzards, have direct effects on crop yields and the vitality of farm animals. In this chapter, three great staple crops (cotton, corn, and wheat) as well as hay of the United States are discussed. The results of the analysis show that hay and corn prices were substantially more responsive to local weather shocks than were cotton and wheat prices. The chapter discusses how the reduction of transactions costs through globalization might potentially mitigate the effects of localized weather shocks.