Privacy Big Data And The Public Good Frameworks For Engagement Book PDF, EPUB Download & Read Online Free

Privacy, Big Data, and the Public Good
Author: Julia Lane, Victoria Stodden, Stefan Bender, Helen Nissenbaum
Publisher: Cambridge University Press
ISBN: 1107067359
Pages: 344
Year: 2014-06-09
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Data access is essential for serving the public good. This book provides new frameworks to address the resultant privacy issues.
Privacy, Big Data, and the Public Good
Author: Julia Lane, Victoria Stodden, Stefan Bender, Helen Nissenbaum
Publisher: Cambridge University Press
ISBN: 1316094456
Pages:
Year: 2014-06-09
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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.
Privacy in Context
Author: Helen Nissenbaum
Publisher: Stanford University Press
ISBN: 0804772894
Pages: 304
Year: 2009-11-24
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Privacy is one of the most urgent issues associated with information technology and digital media. This book claims that what people really care about when they complain and protest that privacy has been violated is not the act of sharing information itself—most people understand that this is crucial to social life —but the inappropriate, improper sharing of information. Arguing that privacy concerns should not be limited solely to concern about control over personal information, Helen Nissenbaum counters that information ought to be distributed and protected according to norms governing distinct social contexts—whether it be workplace, health care, schools, or among family and friends. She warns that basic distinctions between public and private, informing many current privacy policies, in fact obscure more than they clarify. In truth, contemporary information systems should alarm us only when they function without regard for social norms and values, and thereby weaken the fabric of social life.
Group Privacy
Author: Linnet Taylor, Luciano Floridi, Bart van der Sloot
Publisher: Springer
ISBN: 3319466089
Pages: 237
Year: 2016-12-28
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The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies.
Big Data and Social Science
Author: Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane
Publisher: CRC Press
ISBN: 1498751431
Pages: 376
Year: 2016-08-10
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Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
Creating a Data-Driven Organization
Author: Carl Anderson
Publisher: "O'Reilly Media, Inc."
ISBN: 1491916885
Pages: 302
Year: 2015-07-23
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What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in across your company, from analysts and management to the C-Suite and the board. Through interviews and examples from data scientists and analytics leaders in a variety of industries, author Carl Anderson explains the analytics value chain you need to adopt when building predictive business models—from data collection and analysis to the insights and leadership that drive concrete actions. You’ll learn what works and what doesn’t, and why creating a data-driven culture throughout your organization is essential. Start from the bottom up: learn how to collect the right data the right way Hire analysts with the right skills, and organize them into teams Examine statistical and visualization tools, and fact-based story-telling methods Collect and analyze data while respecting privacy and ethics Understand how analysts and their managers can help spur a data-driven culture Learn the importance of data leadership and C-level positions such as chief data officer and chief analytics officer
Implementing Reproducible Research
Author: Victoria Stodden, Friedrich Leisch, Roger D. Peng
Publisher: CRC Press
ISBN: 1466561599
Pages: 448
Year: 2014-04-14
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In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.
The Big Data Agenda
Author: Annika Richterich
Publisher:
ISBN: 1911534971
Pages: 156
Year: 2018-04-13
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This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis. The book assesses in detail one big data research area: biomedical studies, focused on epidemiological surveillance. Specific case studies explore how big data have been used in academic work. The Big Data Agenda concludes that the use of big data in research urgently needs to be considered from the vantage point of ethics and social justice. Drawing upon discourse ethics and critical data studies, Richterich argues that entanglements between big data research and technology/internet corporations have emerged. In consequence, more opportunities for discussing and negotiating emerging research practices and their implications for societal values are needed.
The Cambridge Handbook of Antitrust, Intellectual Property, and High Tech
Author: Roger D. Blair, D. Daniel Sokol
Publisher: Cambridge University Press
ISBN: 1108211178
Pages:
Year: 2017-04-07
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This Cambridge Handbook, edited by Roger D. Blair and D. Daniel Sokol, brings together a group of world-renowned professors in the fields of law and economics to assess the theory and practice of antitrust, intellectual property, and high tech. With the increased globalization of antitrust, a better understanding of how law and economics shape this interface will help academics, policymakers, and practitioners to understand the existing state of academic literature, its limits, and its relevance to real-world antitrust. The book will be an essential resource for anyone seeking to understand academic and policy considerations shaping the world of antitrust, intellectual property, and high tech.
Analytics, Policy, and Governance
Author: Benjamin Ginsberg, Kathy Wagner Hill, Jennifer Bachner
Publisher: Yale University Press
ISBN: 0300208391
Pages: 272
Year: 2017-01-10
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The first available textbook on the rapidly growing and increasingly important field of government analytics This first textbook on the increasingly important field of government analytics provides invaluable knowledge and training for students of government in the synthesis, interpretation, and communication of "big data," which is now an integral part of governance and policy making. Integrating all the major components of this rapidly growing field, this invaluable text explores the intricate relationship of data analytics to governance while providing innovative strategies for the retrieval and management of information.
Quantitative Social Science
Author: Kosuke Imai
Publisher: Princeton University Press
ISBN: 1400885256
Pages: 432
Year: 2017-02-27
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Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors. Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science Provides hands-on instruction using R programming, not paper-and-pencil statistics Includes more than forty data sets from actual research for students to test their skills on Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides
The Big Data-Driven Business
Author: Russell Glass, Sean Callahan
Publisher: John Wiley & Sons
ISBN: 1118889800
Pages: 224
Year: 2014-11-24
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Every corporation in the world is using big data to some degree. The winners in today's data-driven environment create cultures that embrace big data in order to outshine the competition. The Big Data-Driven Business shows what it takes to create a thriving business culture that has intense focus on the customer by analyzing data, by being open to the truths it reveals, and by having the guts to act on those conclusions in order to prevail in the marketplace. The benefits of big data are available to any company, any size, in any industry. In this vital resource, Russell Glass and Sean Callahan offer real-world examples that act as an invaluable guide to establish a system that gathers and analyzes the data being generated by customers for delivering insights and revealing opportunities that can't be realized any other way. Once an effective big data system is established, competitive advantage and outsized shareholder value are bound to follow. The marketplace has entered an era where the customer holds all the cards. With unprecedented choice in both the consumer world and the B2B world, it's imperative that businesses gain a greater understanding of their customers and prospects. Filled with compelling real-world examples, The Big Data-Driven Business clearly demonstrates how leading marketers embrace software platforms that include marketing automation software, customer relationship management systems, data management platforms, and analytics tools to help make sense of customer behavior. The most effective strategy ties together the elements of this software, which is known as the marketing stack. With this insight about the target market, not only can the marketing team serve relevant messages to the right people at the right time, it can also anticipate their needs and perhaps even create the products their customer base didn't even know it wanted. Better information allows for better decisions, better targeting, and better reach. Big data has become an indispensable tool for the most effective marketers in the business, and it's becoming a necessity for businesses that want to thrive. Remaining relevant as the marketplace evolves requires a full understanding and application of big data, and The Big Data-Driven Business provides the practical guidance businesses need.
Federal Statistics, Multiple Data Sources, and Privacy Protection
Author: National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods
Publisher: National Academies Press
ISBN: 0309465370
Pages: 194
Year: 2018-01-27
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The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies’ current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
Religion and the New Technologies
Author: Noreen Herzfeld
Publisher: MDPI
ISBN: 3038425303
Pages: 142
Year: 2018-07-05
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This book is a printed edition of the Special Issue "Religion and the New Technologies" that was published in Religions
Organic Chemistry As a Second Language: First Semester Topics
Author: David R. Klein
Publisher: John Wiley & Sons
ISBN: 1119110661
Pages: 400
Year: 2016-05-02
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Readers continue to turn to Klein's Organic Chemistry as a Second Language: First Semester Topics, 4th Edition because it enables them to better understand fundamental principles, solve problems, and focus on what they need to know to succeed. This edition explores the major principles in the field and explains why they are relevant. It is written in a way that clearly shows the patterns in organic chemistry so that readers can gain a deeper conceptual understanding of the material. Topics are presented clearly in an accessible writing style along with numerous hands-on problem solving exercises.