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Privacy, big data, and the public good : frameworks for engagement / edited by Julia Lane, American Institutes for Research, Washington DC, Victoria Stodden, Columbia University, Stefan Bender, Institute for Employment Research of the German Federal Employment Agency, Helen Nissenbaum, New York University.

Contributor(s): Publisher: New York, NY : Cambridge University Press, 2014Description: xix, 322 pages ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781107637689
  • 1107637686
Subject(s): LOC classification:
  • JC 596 .P747 2014
Contents:
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.
Holdings
Item type Current library Home library Collection Shelving location Call number Status Date due Barcode
Books Books American University in Dubai American University in Dubai Non-fiction Main Collection JC 596 .P747 2014 (Browse shelf(Opens below)) Available 5174456

Includes bibliographical references and index.

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.

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