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This chapter focuses on acts of codification and abstraction as holding the key to economizing on data. Securing of such data economies are further taken as a critical prerequisite of effective communication and, by insinuation, of effective organizational methods. These ideas are brought together in a single united conceptual framework, which is called the I-Space. Economizing on data-processing resources involves moving away from the uncodified end and towards the codified end of the scale, from the inarticulate towards the articulate, from the complex towards the simple. Data-processing economies are by no means an unmixed blessing. A price is paid in terms of lost flexibility, of options sacrificed. The I-Space is a conceptual framework within which the behaviour of information flows can be discovered and, through these, the creation and diffusion of knowledge within selected populations can be understood.

Chapter 1 begins with an introductory section on the data-driven economy and the risks this new type of economy imposes on individuals to provide readers with some necessary background information. It further explains how the regulator responded to the changes in the developing data economy, emphasising the importance of data subject rights within the updated regulatory framework. Subsequently, the chapter clarifies that the aim of this book is to provide a thorough analysis of data subject rights, with a particular concern for their application in the data-driven environments. The chapter also introduces three key concepts that will be used throughout the book: data subjects, data subject (control) rights, and the data-driven economy, as well as delineating the scope of the book and outlining its structure.

This chapter examines Google's aims to dominate the global market for information services and data. Drawing from the suggestion that “information is the new oil of the Internet and the currency of the digital world,” it explores how Google's various endeavors seek to control each facet of the data market: data production, data extraction, data refinement, data infrastructure and distribution, and demand. It shows that there is no equivalent company that has ever been capable of dominance in each facet of the oil economy to the extent that Google leads in the data economy. The chapter also discusses the commodification of information in the modern internet economy and argues that Google's interest in internet freedom and connectivity lies in the fact that its survival (in the political economy sense of the word) depends on getting more and more people online to use its complimentary services.

Chapter 3 establishes a bridge between (a) the general overview of the data-driven economy and the pertaining legal framework, and (b) the specific analysis of data subject control rights. Individual control represents a central notion in philosophical discussions related to people’s autonomy and freedom. In a similar manner, individual control over data plays an important role in the provisions of primary and secondary EU (data protection) law, and has two facets: the normative, meaning that control links back to the values that underpin the entire legal field; and the instrumental, which materialises through the provisions on data subject rights. Despite being a central notion in data protection law, individual control faces many challenges which are rooted in the specific characteristics of the data-driven economy.

More than a decade ago, data, supposedly, became the new “gold” or “oil” of our “age of big data.” If so, then it is critical for societies wishing to secure economic growth and prosperity to devise a data strategy. Like oil, data requires mining and processing before it can become a valuable and usable asset. First, it should be understood that it is almost never those that supply the raw ore that enjoy long-term economic prosperity. Data is a very clean word for coded life, and the consequences of someone having that knowledge, and being able to use it as they see fit, is at the core of both life and the fabric of society. The fact that data is coded life is the reason why it is a criminal dereliction of duty for a community not to develop a data strategy. Further, since data is the raw material for innovation, we have very little reason to believe we know how it will be used in the future. The only thing we can be certain about with data is that for the foreseeable future there will be significant experimentation. The regions where most of the experimentation will occur have higher chances to become the places where more of the economic growth benefits will accrue. The regions that develop a data strategy that lowers the uncertainty around its collection and usage are those that have the higher chances of becoming the locales of experimentation securing their innovation-based growth.