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Privacy, Big Data, and the Public Good: Frameworks for Engagement - GOOD

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Item specifics

Condition
Good: A book that has been read but is in good condition. Very minimal damage to the cover including ...
Brand
Unbranded
Book Title
Privacy, Big Data, and the Public Good: Frameworks for Engagement
MPN
Does not apply
ISBN
9781107637689
Publication Year
2014
Type
Not Available
Format
Trade Paperback
Language
English
Publication Name
Privacy, Big Data, and the Public Good : Frameworks for Engagement
Item Height
0.7in
Author
Victoria Stodden
Item Length
9in
Publisher
Cambridge University Press
Item Width
6in
Item Weight
17 Oz
Number of Pages
339 Pages

About this product

Product Information

The book discusses access to big data for city, state, and federal government agencies and legal, social science, statistical, and technical communities interested in enabling research on big data. The authors' goal is to move the conversation to a vision of what frameworks should and could guide data access.

Product Identifiers

Publisher
Cambridge University Press
ISBN-10
1107637686
ISBN-13
9781107637689
eBay Product ID (ePID)
201609537

Product Key Features

Author
Victoria Stodden
Publication Name
Privacy, Big Data, and the Public Good : Frameworks for Engagement
Format
Trade Paperback
Language
English
Publication Year
2014
Type
Not Available
Number of Pages
339 Pages

Dimensions

Item Length
9in
Item Height
0.7in
Item Width
6in
Item Weight
17 Oz

Additional Product Features

Lc Classification Number
Jc596.P747 2015
Reviews
"'Big data' - the collection, aggregation or federation, and analysis of vast amounts of increasingly granular data - present[s] serious challenges not only to personal privacy but also to the tools we use to protect it. Privacy, Big Data, and the Public Good focuses valuable attention on two of these tools: notice and consent, and de-identification - the process of preventing a person's identity from being linked to specific data. [It] presents a collection of essays from a variety of perspectives, in chapters by some of the heavy hitters in the privacy debate, who make a convincing case that the current framework for dealing with consumer privacy does not adequately address issues posed by big data ... As society becomes more 'datafied' - a term coined to describe the digital quantification of our existence - our privacy is ever more at risk, especially if we continue to rely on the tools that we employ today to protect it. [This book] represents a useful and approachable introduction to these important issues." Science
Table of Content
Part I. Conceptual Framework: Editors' introduction Julia Lane, Victoria Stodden, Stefan Bender and Helen Nissenbaum; 1. Monitoring, datafication, and consent: legal approaches to privacy in the big data context Katherine J. Strandburg; 2. Big data's end run around anonymity and consent Solon Barocas and Helen Nissenbaum; 3. The economics and behavioral economics of privacy Alessandro Acquisti; 4. The legal and regulatory framework: what do the rules say about data analysis? Paul Ohm; 5. Enabling reproducibility in big data research: balancing confidentiality and scientific transparency Victoria Stodden; Part II. Practical Framework: Editors' introduction Julia Lane, Victoria Stodden, Stefan Bender and Helen Nissenbaum; 6. The value of big data for urban science Steven E. Koonin and Michael J. Holland; 7. The new role of cities in creating value Robert Goerge; 8. A European perspective Peter Elias; 9. Institutional controls: the new deal on data Daniel Greenwood, Arkadiusz Stopczynski, Brian Sweatt, Thomas Hardjono and Alex Pentland; 10. The operational framework: engineered controls Carl Landwehr; 11. Portable approaches to informed consent and open data John Wilbanks; Part III. Statistical Framework: Editors' introduction Julia Lane, Victoria Stodden, Stefan Bender and Helen Nissenbaum; 12. Extracting information from big data Frauke Kreuter and Roger Peng; 13. Using statistics to protect privacy Alan F. Karr and Jerome P. Reiter; 14. Differential privacy: a cryptographic approach to private data analysis Cynthia Dwork.
Copyright Date
2015
Target Audience
Scholarly & Professional
Topic
Privacy, Probability & Statistics / General, History & Theory, Research
Lccn
2014-009737
Dewey Decimal
323.44/8
Dewey Edition
23
Illustrated
Yes
Genre
Law, Mathematics, Référence, Political Science

Item description from the seller

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