© 2018 selection and editorial matter, Rob Kitchin, Tracey P. Lauriault and Gavin McArdle; individual chapters, the contributors. There is a long history of governments, businesses, science and citizens producing and utilizing data in order to monitor, regulate, profit from, and make sense of the urban world. Data have traditionally been time-consuming and costly to generate, analyse and interpret, and generally have provided static, often coarse, snapshots of urban phenomena. Recently, however, we have entered the age of big data, with data related to knowing and governing cities increasingly becoming a deluge; a wide, deep torrent of timely, varied, resolute and relational data (Kitchin 2014a; Batty 2016). This has been accompanied by an opening up of state data, and to a much lesser degree, business data, the production of volunteered geographic information, and the emergence of open data cultures and practices (Goodchild 2007; Bates 2012). As a result, evermore aspects of everyday life - work, consumption, travel, communication, leisure - and the worlds we inhabit are being captured and stored as data, made sense of through new data analytics, mediated through data-driven technologies, normalized through data-driven infrastructures, and shared through data infrastructures and data brokers (Amoore 2013; Kitchin 2014b; Offenhuber and Ratti 2014).