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Big Data Is Not a Monolith /

"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 cont...

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Detalles Bibliográficos
Otros Autores: Mattioli, Michael (Editor ), Ekbia, H. R. (Hamid Reza), 1955- (Editor ), Sugimoto, Cassidy R. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, Massachusetts : The MIT Press, [2016]
Colección:Book collections on Project MUSE.
Temas:
Acceso en línea:Texto completo

MARC

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505 0 |a I. Big data and individuals -- 1. Big data, consent, and the future of data protection / Fred H. Cate -- 2. When they are your big data : participatory data practices as a lens on big data / Katie Shilton -- 3. Wrong side of the tracks / Simon DeDeo -- II. Big data and society -- 4. What if everything reveals everything? / Paul Ohm and Scott Peppet -- 5. Big data in the sensor society / Mark Burdon and Mark Andrejevic -- 6. Encoding the everyday: the infrastructure apparatus of social data / Cristina Alaimo and Jannis Kallinikos -- III. Big data and science -- 7. Big genomic data and the state / Jorge L. Contreras -- 8. Trust threads: minimal provenance for data publishing and reuse / Beth Plale, Inna Kouper, Allison Goodwell, and Isuru Suriarachchi -- 9. Can we anticipate some unintended consequences of big data? / Kent R. Anderson -- 10. The data gold rush in higher education / Jevin D. West and Jason Portenoy -- IV. Big data and organizations -- 11. Obstacles on the road to corporate data responsibility / M. Lynne Markus -- 12. Will big data diminish the role of humans in decision making? / Michael Bailey -- 13. Big data in medicine: potential, reality, and implications / Dan Sholler, Diane E. Bailey, and Julie Rennecker -- 14. Hal the innovator: big data and its use by artificial intelligence / Ryan Abbott. 
520 3 |a "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 individual 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." 
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