Big Data Is Not a Monolith (Information Policy)

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9780262035057: Big Data Is Not a Monolith (Information Policy)

Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies.

The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, "data harm," and decision making.

ContributorsRyan Abbott, Cristina Alaimo, Kent R. Anderson, Mark Andrejevic, Diane E. Bailey, Mike Bailey, Mark Burdon, Fred H. Cate, Jorge L. Contreras, Simon DeDeo, Hamid R. Ekbia, Allison Goodwell, Jannis Kallinikos, Inna Kouper, M. Lynne Markus, Michael Mattioli, Paul Ohm, Scott Peppet, Beth Plale, Jason Portenoy, Julie Rennecker, Katie Shilton, Dan Sholler, Cassidy R. Sugimoto, Isuru Suriarachchi, Jevin D. West

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About the Author:

Cassidy R. Sugimoto is Associate Professor in the School of Informatics and Computing at Indiana University Bloomington and the coeditor of Beyond Bibliometrics (MIT Press). Hamid R. Ekbia is Associate Professor in the Schools of Informatics and Computing, Cognitive Science, and International Studies at Indiana University Bloomington. Michael Mattioli is Associate Professor at the Indiana University Maurer School of Law.

Review:

Big data pervades and crosses organizations and domains, posing multiple challenges, yet these challenges are dwarfed by the opportunities and issues posed by big data analytics (BDA). For a researcher working on BDA, this volume opens multiple perspectives on an amazingly rich cross-section of those and explores what to do about them.

(Alan Porter, codirector of the Program in Science, Technology & Innovation Policy (STIP), Georgia Tech)

This book combines expertise from different areas of scholarship to give valuable insights into what big data is doing, what it can do, and what it should be allowed to do. It is essential reading for those wishing to understand the widespread societal implications of the big data revolution.

(Mike Thelwall, Professor of Information Science, University of Wolverhampton)

Big Data Is Not a Monolith is required reading for those who find themselves in the thrall of big data but want to move beyond the hype to understand the social context of the current big data computerization movement. The collected authors ably grapple with how big data as a socio-technical system contributes to knowledge, shapes human behavior and choices, and has become increasingly integral to our social, legal, political, and economic systems.

(Eric T. Meyer, Professor of Social Informatics, University of Oxford; coauthor of Knowledge Machines: Digital Transformations of the Sciences and Humanities)

Well informed (up to date references), well written, an interesting read. This text is highly recommended, for all readers and practitioners with a serious interest in Big Data Analytics (BDA). Simply excellent!

(British Computer Society)

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Book Description MIT Press Ltd, United States, 2016. Hardback. Book Condition: New. Language: English . Brand New Book. Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies.The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data s ramifications. The contributors look at big data s effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, data harm, and decision making.ContributorsRyan Abbott, Cristina Alaimo, Kent R. Anderson, Mark Andrejevic, Diane E. Bailey, Mike Bailey, Mark Burdon, Fred H. Cate, Jorge L. Contreras, Simon DeDeo, Hamid R. Ekbia, Allison Goodwell, Jannis Kallinikos, Inna Kouper, M. Lynne Markus, Michael Mattioli, Paul Ohm, Scott Peppet, Beth Plale, Jason Portenoy, Julie Rennecker, Katie Shilton, Dan Sholler, Cassidy R. Sugimoto, Isuru Suriarachchi, Jevin D. West. Bookseller Inventory # AAS9780262035057

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