Coverart for item
The Resource 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

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

Label
Privacy, Big Data, and the Public Good : Frameworks for Engagement
Title
Privacy, Big Data, and the Public Good
Title remainder
Frameworks for Engagement
Statement of responsibility
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
Editor
Subject
Language
eng
Summary
Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In order to achieve this goal, researchers must have access to this data - raising important privacy questions. What are the ethical and legal requirements? What are the rules of engagement? What are the best ways to provide access while also protecting confidentiality? Are there reasonable mechanisms to compensate citizens for privacy loss? The goal of this book is to answer some of these questions. The book's authors paint an intellectual landscape that includes legal, economic, and statistical frameworks. The authors also identify new practical approaches that simultaneously maximize the utility of data access while minimizing information risk. -- Back cover
Cataloging source
DLC
Dewey number
323.44/8
Index
no index present
Language note
Text in English
LC call number
JC596
LC item number
.P747 2014
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Lane, Julia I.
  • Stodden, Victoria
  • Bender, Stefan
  • Nissenbaum, Helen.
http://library.link/vocab/subjectName
  • Privacy, Right of
  • Research
  • Big data
  • Common good
Label
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
Instantiates
Publication
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Monitoring, Datafication, and Consent: Legal Approaches to Privacy in the Big Data Context / Katherine J. Strandburg -- Big Data's End Run Around Anonymity and Consent / Solon Barocas and Helen Nissenbaum -- The Economics and Behavioral Economics of Privacy / Alessandro Acquisti -- Changing the Rules: General Principles for Data Use and Analysis / Paul Ohm -- Enabling Reproducibility in Big Data Research: Balancing Confidentiality and Scientific Transparency / Victoria Stodden -- The Value of Big Data for Urban Science / Steven E. Koonin and Michael J. Holland -- Data for the Public Good: Challenges and Barriers in the Context of Cities / Robert M. Goerge -- A European Perspective on Research and Big Data Analysis / Peter Elias -- The New Deal on Data: A Framework for Institutional Controls / Daniel Greenwood et. al -- Engineered Controls for Dealing with Big Data / Carl Landwehr -- Portable Approaches to Informed Consent and Open Data / John Wilbanks -- Extracting Information from Big Data: Issues of Measurement, Inference and Linkage / Frauke Kreuter and Roger D. Peng -- Using Statistics to Protect Privacy / Alan F. Karr and Jerome P. Reiter -- Differential Privacy: A Cryptographic Approach to Private Data Analysis / Cynthia Dwork
Control code
876370806
Dimensions
24 cm
Extent
xix, 322 pages
Isbn
9781107637689
Isbn Type
(pbk. : alk. paper)
Lccn
2014009737
Media category
unmediated
Media MARC source
rdamedia.
Media type code
  • n
System control number
(OCoLC)876370806
Label
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
Publication
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Monitoring, Datafication, and Consent: Legal Approaches to Privacy in the Big Data Context / Katherine J. Strandburg -- Big Data's End Run Around Anonymity and Consent / Solon Barocas and Helen Nissenbaum -- The Economics and Behavioral Economics of Privacy / Alessandro Acquisti -- Changing the Rules: General Principles for Data Use and Analysis / Paul Ohm -- Enabling Reproducibility in Big Data Research: Balancing Confidentiality and Scientific Transparency / Victoria Stodden -- The Value of Big Data for Urban Science / Steven E. Koonin and Michael J. Holland -- Data for the Public Good: Challenges and Barriers in the Context of Cities / Robert M. Goerge -- A European Perspective on Research and Big Data Analysis / Peter Elias -- The New Deal on Data: A Framework for Institutional Controls / Daniel Greenwood et. al -- Engineered Controls for Dealing with Big Data / Carl Landwehr -- Portable Approaches to Informed Consent and Open Data / John Wilbanks -- Extracting Information from Big Data: Issues of Measurement, Inference and Linkage / Frauke Kreuter and Roger D. Peng -- Using Statistics to Protect Privacy / Alan F. Karr and Jerome P. Reiter -- Differential Privacy: A Cryptographic Approach to Private Data Analysis / Cynthia Dwork
Control code
876370806
Dimensions
24 cm
Extent
xix, 322 pages
Isbn
9781107637689
Isbn Type
(pbk. : alk. paper)
Lccn
2014009737
Media category
unmediated
Media MARC source
rdamedia.
Media type code
  • n
System control number
(OCoLC)876370806

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