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 include: 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.T.T. Tai, H. U
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