We live in a data-driven world. How we make sense of the world is increasingly mediated through data-rich technologies, not based simply on our everyday experiences, practical knowledge and learned ideas. Many of our activities produce data and are shaped by data-driven processes and systems. How society is governed and organizations managed is evermore technocratic in nature, dependent on big data streams and mass dataveillance. Our economies and practices of work are transforming through the rise in digital labour, automation, platform ecosystems and surveillance capitalism. As digital technologies come to be further embedded into the fabric of our infrastructures, environments and social systems, and actively mediate our everyday lives, our reliance on data will intensify. Our future is one saturated with and molded by data.

My aim in this book has been to shine a critical light onto the nature and life of data and to chart the rapid unfolding and impact of data-driven technologies, processes and practices on how we live our lives. To use my own professional experience of working with data, creating data infrastructures and data policy, and reflecting on data-driven technologies and their consequences, to provide data stories and analysis that reveal the praxes and politics in the life of data and how we live with data.

What those stories revealed is that up until relatively recently, we have focused little conceptual and critical attention on data themselves. Instead, we have tended to think about and treat them in quite technical terms: focusing on how to collect, handle, process, analyze, store and share them. Data were understood to be the building blocks for information and knowledge, and what critical attention were paid to them generally concerned issues such as access and data quality. In the last couple of decades, it has become apparent that data are not simply a raw material that are mined, assembled and worked upon through technical processes. Rather, data are produced within a socio-technical context, their life cycle influenced by a range of factors. Data do not pre-exist their generation and are not teleological, absolute and essential (pre-determined, natural and invariable). Data are cooked and are contingent and relational; mutable under the conditions of their production and use.