Taxation of Big Data

This book has the merit of being the first book analysing different aspects of data taxation from a wide perspective encompassing not only tax law but also other significant issues related to data, such as data protection and economic inefficiencies. The main aim is to provide data-specific solutions to data-driven problems. In the midst of a number of critical issues and a great deal of uncertainty currently reigning in the field, the authors attempt to put forward easy-to-implement and efficient proposals on the basis of an interdisciplinary analysis. The core idea of this book consists of segregating the utilisation of data into four different yet interdependent steps and constructing the tax law analysis on top of these four corner stones. Step one, occurring in the generation and collection phases of the datas life cycle, comprises the digital barter and other collection of data. Step two, taking place during the processing and analytics phasesof the datas life cycle, consists of microwork. Step three, situated in the storage, processing, analytics and use phases of the datas life cycle, encompasses aggregation and internal use of data. Step four, materialising during the distribution and use phases of the datas life cycle, covers sale of data, transfer of data and granting the right to use a database. The main issues occurring in each of the four steps are analysed separately, and yet interdependently, with an emphasis on international tax law. The book also comprises a VAT analysis; suggestion of a new type of tax, namely data collection tax; and a brief opinion on a potential future robo-data tax. The subjects explored in this book are of interest for researchers, lawyers as well as tax administrations. Albeit being an academic publication, the developments made in this contribution are also relevant for the general public. After all, data, the youngest intangible, constitute the raw material of the fourth industrial revolution; and their use and taxation affect each and every citizen!