Big Data, Big Challenges in Evidence-Based Policy Making

Big Data, Big Challenges in Evidence-Based Policy Making is a multi-disciplinary study of how to glean insights from massive data sets to make better public policy decisions. Using a combination of explanatory material, specific examples, and practical suggestions, the book teaches readers how to preserve, use, and publish big data. Each chapter provides real-life examples of how big data can be used in policy making. The book also provides practical insights from archivists and librarians who are on the forefront of preserving data and helping researchers find needed data. To complete the discussion of big data, the book provides a frank and nuanced discussion of privacy risks involved with big data. It also examines the political constraints on how to regulate privacy. In addition, the book offers a comparative review of privacy by examining the different privacy protections in the US and the EU, as well as the delicate system of trading private data between nations.

This book can be used to supplement upper level law school courses as well as courses on public health, economics, political science, environmental studies, and information science.

The contributors are: Margaret O'Neill Adams, Judith Amsalem, Paula Avila-Guillen, Ana Ayala, Tanya Baytor, Josh Blackman, Linda K. Breggin, Dianne Callan, Christin Cave, Kristofer A. Ekdahl, Francine E. Friedman, Aliza Glasner, Carole Roan Gresenz, James Grimmelmann, Mark D. Johnson, Leslie Johnston, Susan C. Kim, John D. Kraemer, William G. LeFurgy, Jared Lyle, Kathryn Mengerink, Elizabeth Moss, Catherine Powell, Jason S. Roffenbender, Joshua C. Teitelbaum, Matthew C. Thomas, and Zachary Turk.