Research Handbook on Big Data Law

This state-of-the-art Research Handbook provides an overview of research into, and the scope of current thinking in, the field of big data analytics and the law. It contains a wealth of information to survey the issues surrounding big data analytics in legal settings, as well as legal issues concerning the application of big data techniques in different domains.

Featuring contributions from a variety of expert scholars, this is an interdisciplinary dialogue addressing big data analytics, tools and techniques and the societal impact of the field. Chapters analyze both cases anchored in a particular legal system (such as anti-corruption in China) and big data law approaches relevant across multiple practice areas: including machine learning within law, legal information retrieval, natural language processing and e-discovery. It also offers original insights from industry project reports that use big data law techniques in interesting, new ways.

Providing a unique and interdisciplinary blend of analysis, this Research Handbook will be a key resource for legal scholars and students researching in areas such as criminal, tax, copyright and administrative law. It will also prove useful for practicing lawyers wanting to get a sense of the legal practice of the future, as well as law-makers thinking about the use of big data law techniques in government policy.

Edited by Roland Vogl, Executive Director and Lecturer in Law, CodeX - The Stanford Center for Legal Informatics, Stanford Law School, US