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Big Data   Tags: big data, data  

This is a guide to resources relating to Big Data in the Moritz Law Library and OSU Libraries.
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Big Data

Thanks for visiting the Moritz Law Library Research Guide collection!

These are print materials relating to Big Data that are available at the Moritz Law Library, with links to the OSU Libraries catalog.

Reference Librarians staff the Reference Desk on the second floor of the Law Library and also may be contacted by telephone at (614) 292-9463 or by e-mail at lawlibref@osu.edu.

 

Books in the Moritz Law Library

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Big Data : a Business and Legal Guide - James R. Kalyvas; Michael R. Overly
Call Number: KF390.5.C6 K35 2015
ISBN: 1466592370
Publication Date: 2014-09-03
Big Data: A Business and Legal Guide supplies a clear understanding of the interrelationships between Big Data, the new business insights it reveals, and the laws, regulations, and contracting practices that impact the use of the insights and the data. Providing business executives and lawyers (in-house and in private practice) with an accessible primer on Big Data and its business implications, this book will enable readers to quickly grasp the key issues and effectively implement the right solutions to collecting, licensing, handling, and using Big Data. Taking a cross-disciplinary approach, the book will help executives, managers, and counsel better understand the interrelationships between Big Data, decisions based on Big Data, and the laws, regulations, and contracting practices that impact its use. After reading this book, you will be able to think more broadly about the best way to harness Big Data in your business and establish procedures to ensure that legal considerations are part of the decision.

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Big Data at Work - Thomas H. Davenport
Call Number: HD38.7 .D379 2014
ISBN: 9781422168165
Publication Date: 2014-02-25
Go ahead, be skeptical about big data. The author was - at first. When the term "big data" first came on the scene, bestselling author Tom Davenport ( Competing on Analytics, Analytics at Work ) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means-and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold.This book will help you understand: - Why big data is important to you and your organization - What technology you need to manage it - How big data could change your job, your company, and your industry - How to hire, rent, or develop the kinds of people who make big data work - The key success factors in implementing any big data project - How big data is leading to a new approach to managing analyticsWith dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities-from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.

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Big Data Computing - Rajendra Akerkar (Editor)
Call Number: QA76.9.D3 B52796 2014
ISBN: 9781466578371
Publication Date: 2013-12-05
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches.

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Big Data, Little Data, No Data : Scholarship in the Networked World - Christine L. Borgman
Call Number: AZ195 .B66 2015
ISBN: 9780262028561
Publication Date: 2015-01-02
"Big Data" is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six "provocations" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.

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Data and Goliath : this hidden battles to collect your data and control your world - Bruce Schneier
Call Number: HM846 .S362 2015
ISBN: 9780393244816
Publication Date: 2015-03-02
Your cell phone provider tracks your location and knows who's with you. Your online and in-store purchasing patterns are recorded, and reveal if you're unemployed, sick, or pregnant. Your e-mails and texts expose your intimate and casual friends. Google knows what you're thinking because it saves your private searches. Facebook can determine your sexual orientation without you ever mentioning it. The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the prices we're offered. Governments use surveillance to discriminate, censor, chill free speech, and put people in danger worldwide. And both sides share this information with each other or, even worse, lose it to cybercriminals in huge data breaches. Much of this is voluntary: we cooperate with corporate surveillance because it promises us convenience, and we submit to government surveillance because it promises us protection. The result is a mass surveillance society of our own making. But have we given up more than we've gained? In Data and Goliath, security expert Bruce Schneier offers another path, one that values both security and privacy. He shows us exactly what we can do to reform our government surveillance programs and shake up surveillance-based business models, while also providing tips for you to protect your privacy every day. You'll never look at your phone, your computer, your credit cards, or even your car in the same way again.

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Data Mining and Knowledge Discovery for Big Data - Wesley W. Chu (Editor)
Call Number: QA76.9 .D343 C58 2014
ISBN: 9783642408366
Publication Date: 2013-10-09
The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.

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Data Protection in a Profiled World - Serge Gutwirth (Editor); Yves Poullet (Editor); Paul de Hert (Editor)
Call Number: K3264.C65 C66 2010
ISBN: 9789048188642
Publication Date: 2010-08-03
One of the most challenging issues facing our current information society is the accelerating accumulation of data trails in transactional and communication systems, which may be used not only to profile the behavior of individuals for commercial, marketing and law enforcement purposes, but also to locate and follow things and actions. Data mining, convergence, interoperability, ever- increasing computer capacities and the extreme miniaturization of the hardware are all elements which contribute to a major contemporary challenge: the profiled world. This interdisciplinary volume offers twenty contributions that delve deeper into some of the complex but urgent questions that this profiled world addresses to data protection and privacy. The chapters of this volume were all presented at the second Conference on Privacy and Data Protection (CPDP2009) held in Brussels in January 2009 (www.cpdpconferences.org). The yearly CPDP conferences aim to become Europe’s most important meeting where academics, practitioners, policy-makers and activists come together to exchange ideas and discuss emerging issues in information technology, privacy and data protection and law. This volume reflects the richness of the conference, containing chapters by leading lawyers, policymakers, computer, technology assessment and social scientists. The chapters cover generic themes such as the evolution of a new generation of data protection laws and the constitutionalization of data protection and more specific issues like security breaches, unsolicited adjustments, social networks, surveillance and electronic voting. This book not only offers a very close and timely look on the state of data protection and privacy in our profiled world, but it also explores and invents ways to make sure this world remains a world we want to live in.

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Electronically Stored Information - David R. Matthews
Call Number: KF8902.E42 M39 2013
ISBN: 9781439877265
Publication Date: 2012-07-17
Although we live in a world where we are surrounded in an ever-deepening fog of data, few understand how the data are created, where data are stored, or how to retrieve or destroy data. Accessible to readers at all levels of technical understanding, Electronically Stored Information: The Complete Guide to Management, Understanding, Acquisition, Storage, Search, and Retrieval covers all aspects of electronic data and how it should be managed. Using easy-to-understand language, the book explains: exactly what electronic information is, the different ways it can be stored, why we need to manage it from a legal and organizational perspective, who is likely to control it, and how it can and should be acquired to meet legal and managerial goals.

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Knowledge Discovery from Legal Databases - Andrew Stranieri; John Zeleznikow
Call Number: K87 .S77 2005
ISBN: 1402030363
Publication Date: 2005-06-01
Knowledge Discovery from Legal Databases is the first text to describe data mining techniques as they apply to law. Law students, legal academics and applied information technology specialists are guided thorough all phases of the knowledge discovery from databases process with clear explanations of numerous data mining algorithms including rule induction, neural networks and association rules. Throughout the text, assumptions that make data mining in law quite different to mining other data are made explicit. Issues such as the selection of commonplace cases, the use of discretion as a form of open texture, transformation using argumentation concepts and evaluation and deployment approaches are discussed at length.

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Pocket Data Mining - Mohamed Medhat Gaber; Frédéric Stahl; Joao Bartolo Gomes
Call Number: QA76.9.D343 G33 2013
ISBN: 9783319027104
Publication Date: 2013-10-28
Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

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The Power of Knowledge : ethical, legal and technological aspects of data mining and group profiling in epidemiology - Bart Custers
Call Number: K3264.C65 C87 2004
ISBN: 9058500853
Publication Date: 2005-01-01
With the rise of information and communication technologies, large amounts of data are being generated and stored in databases. In order to get a better grip on these large amounts of data, serious efforts are being made to discover patterns and relations in the data with the help of new techniques. One of these techniques is data mining, an automated analysis aimed at finding patterns and relations in data. Through data mining, characteristics may be ascribed to individuals and groups, thus yielding personal profiles or group profiles. In the case of medical data, profiles may be used in epidemiology in order to solve or contribute to solving aetiological, diagnostic, prognostic, or therapeutic problems. However, the same information may be used for determining selection criteria, such as for insurances, jobs, or loans. The information may also be stigmatising or disturbing. Whereas the collection and processing of personal data is subjected to data protection legislation in Europe, this is not necessarily the case for group profiles. As a result, people are increasingly being judged as members of groups, for instance, as people with the same postcode, consumers of peanut butter, or DNA carriers. The Power of Knowledge offers an in-depth analysis of the possible moral problems of data mining and group profiling in medical data. After an analysis of the moral problems, legal and technological solutions are critically discussed. Legal solutions may be found in data protection law, public health law, and anti-discrimination law. Technological solutions based on cryptography may involve restricting the coupling of data and limiting the identifiability of data. Taking a multidisciplinary approach, the author shows how ethics, law, and technology can supplement each other when providing solutions for the problems of data mining and group profiling.

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Preventing litigation : an early warning system to get big value out of big data - Nelson E. Brestoff; William H. Inmon
Call Number: K1005 .B747 2015
ISBN: 9781631573156
Publication Date: 2015-09-01
Preventing Litigation, for the first time, explains how to build an early warning system to identify the risk of litigation before the damage is done, and proves that there is big value in less litigation. The authors are subject matter experts, one in litigation, the other in computer science, and each has more than four decades of training and experience in their respective fields. Together, they present a way forward to a transformative revolution for the slow- moving world of law for the benefit of the fast-paced environment of the business world.

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Privacy and Surveillance with New Technologies - Peter P. Swire; Kenesa Ahmad (Editor)
Call Number: KF5399 .P75 2012
ISBN: 9781617700583
Publication Date: 2012-09-01
Never has privacy been more important than today, when businesses can track every click of your mouse and governments can collect vast amounts of information on citizens without their knowledge-all thanks to technological innovation. New technologies have made our lives better but at what cost to privacy? What does privacy mean in the Internet age? How do we reap the benefits of new technology while guarding our privacy?

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Privacy, Due Process and the Computational Turn - Mireille Hildebrandt (Editor); Katja De Vries (Editor)
Call Number: K487.T4 P75 2013
ISBN: 9780415644815
Publication Date: 2013-05-22
Privacy, Due process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology engages with the rapidly developing computational aspects of our world - including data mining, behavioural advertising, iGovernment, profiling for intelligence, customer relationship management, smart search engines, personalized news feeds, and so on - in order to consider their implications for the assumptions on which our legal framework has been built. The contributions to this volume focus on the issue of privacy, which is often equated with data privacy and data security, location privacy, anonymity, pseudonymity, unobservability, and unlinkability. Here, however, the extent to which predictive and other types of data analytics operate in ways that may - or may not - violate privacy is rigorously taken up, both technologically and legally, in order to open up new possibilities for considering, and contesting, how we are increasingly being correlated and categorized.

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Privacy in the Age of Big Data - Theresa M. Payton; Theodore Claypoole; Howard A. Schmidt (Foreword by)
Call Number: KF1262 .P39 2014
ISBN: 9781442225459
Publication Date: 2014-01-16
Digital data collection and surveillance gets more pervasive and invasive by the day; but the best ways to protect yourself and your data are all steps you can take yourself. The devices we use to get just-in-time coupons, directions when we re lost, and maintain connections with loved ones no matter how far away they are, also invade our privacy in ways we might not even be aware of. Our devices send and collect data about us whenever we use them, but that data is not safeguarded the way we assume it would be. Privacy is complex and personal. Many of us do not know the full extent to which data is collected, stored, aggregated, and used. As recent revelations indicate, we are subject to a level of data collection and surveillance never before imaginable. While some of these methods may, in fact, protect us and provide us with information and services we deem to be helpful and desired, others can turn out to be insidious and over-arching. Privacy in the Age of Big Data highlights the many positive outcomes of digital surveillance and data collection while also outlining those forms of data collection to which we may not consent, and of which we are likely unaware. Payton and Claypoole skillfully introduce readers to the many ways we are watched, and how to adjust our behaviors and activities to recapture our privacy. The authors suggest the tools, behavior changes, and political actions we can take to regain data and identity security. Anyone who uses digital devices will want to read this book for its clear and no-nonsense approach to the world of big data and what it means for all of us.

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Too Big to Ignore - Phil Simon
Call Number: QA76.9.D343 S594 2013
ISBN: 9781118638170
Publication Date: 2013-03-18
In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate. Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.

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