The generation and use of data in society has seen exponential growth in recent years. The emergent field of data science, concerned with understanding and analyzing this data, can be applied to applications spanning from healthcare and urban planning to smart household devices. The legal questions which accompany the rise of these technologies, however, remains underexplored. Breaking new ground this Research Handbook maps the legal implications of the emergence of data science.
Drawing on comparative perspectives, this Research Handbook approaches the subject from different legal domains, considering the possibilities and limitations of the current legal framework. Reflecting on whether further regulation is needed to address the ethical and legal problems raised by data science, the contributors examine how the practice is, and should be, regulated and how it influences the law, judiciary, and legal research. The book makes a vital contribution to the emerging field of data science and law as a discipline, and covers data science methodologies and tools essential for both legal practice and scholarship.
The Research Handbook in Data Science and Law will be an important resource for students interested in data and technology law, as well as for legal scholars and practitioners in the field. Data scientists seeking an introduction to the law surrounding the field will also find this Research Handbook invaluable.
Contributors: A. Berlee, C. Busch, A. Carlson, M.O. Cuevas, B. Custers, A. Daly, A. De Franceschi, W. Kaufmann, A. Klop, S. Kreifels, K.M. Kryla-Cudna, A.J.F. Lafarre, V. Mak, M. Mattioli, R. Nurullaev, R. Podszun, M.G. Porcedda, C. Prins, S. Ranchordas, R. Russo, K.K.E.C.T. Swinnen, P. Szulewski, E. Tjong Tjin Tai, H. Ursic, C.F. van der Elst, B.J. van Ettekoven, T. Van Geelen, D. Wall, V.Z. Zencovich.
Edited by Vanessa Mak, Eric Tjong Tjin Tai, Tilburg University and Anna Berlee, Utrecht University, the Netherlands.