Ethical Reasoning in Big Data

An Exploratory Analysis
Author: Jeff Collmann,Sorin Adam Matei
Publisher: Springer
ISBN: 3319284223
Category: Computers
Page: 192
View: 6652

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This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public’s trust in the abilities of particular scientists and scientific institutions constitutes one of this book’s major themes. The advent of the Internet, the mass digitization of research information, and social media brought about, among many other things, the ability to harvest – sometimes implicitly – a wealth of human genomic, biological, behavioral, economic, political, and social data for the purposes of scientific research as well as commerce, government affairs, and social interaction. What type of ethical dilemmas did such changes generate? How should scientists collect, manipulate, and disseminate this information? The effects of this revolution and its ethical implications are wide-ranging. This book includes the opinions of myriad investigators, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in action, the book offers a range of observations, lessons learned, reasoning tools, and suggestions for institutional practice to promote responsible big data research on human affairs. It caters to a broad audience of educators, researchers, and practitioners. Educators can use the volume in courses related to big data handling and processing. Researchers can use it for designing new methods of collecting, processing, and disseminating big data, whether in raw form or as analysis results. Lastly, practitioners can use it to steer future tools or procedures for handling big data. As this topic represents an area of great interest that still remains largely undeveloped, this book is sure to attract significant interest by filling an obvious gap in currently available literature.

At the Crossroads: Lessons and Challenges in Computational Social Science


Author: Javier Borge-Holthoefer,Yamir Moreno,Taha Yasseri
Publisher: Frontiers Media SA
ISBN: 288945021X
Category:
Page: N.A
View: 1170

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The interest of physicists in economic and social questions is not new: for over four decades, we have witnessed the emergence of what is called nowadays “sociophysics” and “econophysics”, vigorous and challenging areas within the wider “Interdisciplinary Physics”. With tools borrowed from Statistical Physics and Complexity, this new area of study have already made important contributions, which in turn have fostered the development of novel theoretical foundations in Social Science and Economics, via mathematical approaches, agent-based modelling and numerical simulations. From these foundations, Computational Social Science has grown to incorporate as well the empirical component --aided by the recent data deluge from the Web 2.0 and 3.0--, closing in this way the experiment-theory cycle in the best tradition of Physics.

The Big Data Agenda

Data Ethics and Critical Data Studies
Author: Annika Richterich
Publisher: N.A
ISBN: 9781911534976
Category: Social Science
Page: 156
View: 9054

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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.

Big Data For Small Business For Dummies


Author: Bernard Marr
Publisher: John Wiley & Sons
ISBN: 1119027039
Category: Business & Economics
Page: 256
View: 8891

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Capitalise on big data to add value to your small business Written by bestselling author and big data expert Bernard Marr, Big Data For Small Business For Dummies helps you understand what big data actually is—and how you can analyse and use it to improve your business. Free of confusing jargon and complemented with lots of step-by-step guidance and helpful advice, it quickly and painlessly helps you get the most from using big data in a small business. Business data has been around for a long time. Unfortunately, it was trapped away in overcrowded filing cabinets and on archaic floppy disks. Now, thanks to technology and new tools that display complex databases in a much simpler manner, small businesses can benefit from the big data that's been hiding right under their noses. With the help of this friendly guide, you'll discover how to get your hands on big data to develop new offerings, products and services; understand technological change; create an infrastructure; develop strategies; and make smarter business decisions. Shows you how to use big data to make sense of user activity on social networks and customer transactions Demonstrates how to capture, store, search, share, analyse and visualise analytics Helps you turn your data into actionable insights Explains how to use big data to your advantage in order to transform your small business If you're a small business owner or employee, Big Data For Small Business For Dummies helps you harness the hottest commodity on the market today in order to take your company to new heights.

Data Fluency

Empowering Your Organization with Effective Data Communication
Author: Zach Gemignani,Chris Gemignani,Richard Galentino,Patrick Schuermann
Publisher: John Wiley & Sons
ISBN: 1118851005
Category: Computers
Page: 288
View: 9124

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A dream come true for those looking to improve their data fluency Analytical data is a powerful tool for growing companies, but what good is it if it hides in the shadows? Bring your data to the forefront with effective visualization and communication approaches, and let Data Fluency: Empowering Your Organization with Effective Communication show you the best tools and strategies for getting the job done right. Learn the best practices of data presentation and the ways that reporting and dashboards can help organizations effectively gauge performance, identify areas for improvement, and communicate results. Topics covered in the book include data reporting and communication, audience and user needs, data presentation tools, layout and styling, and common design failures. Those responsible for analytics, reporting, or BI implementation will find a refreshing take on data and visualization in this resource, as will report, data visualization, and dashboard designers. Conquer the challenge of making valuable data approachable and easy to understand Develop unique skills required to shape data to the needs of different audiences Full color book links to bonus content at juiceanalytics.com Written by well-known and highly esteemed authors in the data presentation community Data Fluency: Empowering Your Organization with Effective Communication focuses on user experience, making reports approachable, and presenting data in a compelling, inspiring way. The book helps to dissolve the disconnect between your data and those who might use it and can help make an impact on the people who are most affected by data. Use Data Fluency today to develop the skills necessary to turn data into effective displays for decision-making.

Children in Charted Designs


Author: Lindberg Press
Publisher: Courier Corporation
ISBN: 9780486259413
Category: Crafts & Hobbies
Page: 48
View: 6919

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Forty-six delightful charted needlework designs depicting children playing with pets and toys, flying kites, making snowmen, picking flowers, and more. 46 black-and-white color-coded charts. 16 how-to diagrams.

Big Data Analytics in the Social and Ubiquitous Context

5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers
Author: Martin Atzmueller,Alvin Chin,Frederik Janssen,Immanuel Schweizer,Christoph Trattner
Publisher: Springer
ISBN: 3319290096
Category: Computers
Page: 187
View: 2359

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The 9 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: The 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and the First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, which were held on September 15, 2014, in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5th International Workshop on Modeling Social Media (MSM 2014) that was held on April 8, 2014 in conjunction with ACM WWW in Seoul, Korea.

Ethics of Big Data

Balancing Risk and Innovation
Author: Kord Davis
Publisher: "O'Reilly Media, Inc."
ISBN: 1449357490
Category: Computers
Page: 82
View: 868

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What are your organization’s policies for generating and using huge datasets full of personal information? This book examines ethical questions raised by the big data phenomenon, and explains why enterprises need to reconsider business decisions concerning privacy and identity. Authors Kord Davis and Doug Patterson provide methods and techniques to help your business engage in a transparent and productive ethical inquiry into your current data practices. Both individuals and organizations have legitimate interests in understanding how data is handled. Your use of data can directly affect brand quality and revenue—as Target, Apple, Netflix, and dozens of other companies have discovered. With this book, you’ll learn how to align your actions with explicit company values and preserve the trust of customers, partners, and stakeholders. Review your data-handling practices and examine whether they reflect core organizational values Express coherent and consistent positions on your organization’s use of big data Define tactical plans to close gaps between values and practices—and discover how to maintain alignment as conditions change over time Maintain a balance between the benefits of innovation and the risks of unintended consequences

Handbook of Big Data Technologies


Author: Albert Y. Zomaya,Sherif Sakr
Publisher: Springer
ISBN: 331949340X
Category: Computers
Page: 895
View: 4607

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This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms. Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. It also dives into the details of implementing Big SQL query engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and exploratory ad hoc analysis in addition to structured querying and pattern matching techniques. Part Three presents a comprehensive overview of large scale graph processing. It covers the most recent research in large scale graph processing platforms, introducing several scalable graph querying and mining mechanisms in domains such as social networks. Part Four details novel applications that have been made possible by the rapid emergence of Big Data technologies such as Internet-of-Things (IOT), Cognitive Computing and SCADA Systems. All parts of the book discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains. Designed for researchers, IT professionals and graduate students, this book is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and future of the field.

Social Science Research

Principles, Methods, and Practices
Author: Anol Bhattacherjee
Publisher: CreateSpace
ISBN: 9781475146127
Category: Science
Page: 156
View: 3536

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This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.

Doing Data Science

Straight Talk from the Frontline
Author: Cathy O'Neil,Rachel Schutt
Publisher: "O'Reilly Media, Inc."
ISBN: 144936389X
Category: Computers
Page: 408
View: 7107

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Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Encyclopedia of Information Science and Technology, Third Edition


Author: Khosrow-Pour, Mehdi
Publisher: IGI Global
ISBN: 1466658894
Category: Computers
Page: 10384
View: 7270

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"This 10-volume compilation of authoritative, research-based articles contributed by thousands of researchers and experts from all over the world emphasized modern issues and the presentation of potential opportunities, prospective solutions, and future directions in the field of information science and technology"--Provided by publisher.

Frontiers in Massive Data Analysis


Author: National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Applied and Theoretical Statistics,Committee on the Analysis of Massive Data
Publisher: National Academies Press
ISBN: 0309287812
Category: Mathematics
Page: 190
View: 8843

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Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale--terabytes and petabytes--is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge--from computer science, statistics, machine learning, and application disciplines--that must be brought to bear to make useful inferences from massive data.

Big Data and Social Science

A Practical Guide to Methods and Tools
Author: Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane
Publisher: CRC Press
ISBN: 1498751431
Category: Mathematics
Page: 376
View: 986

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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.

Internet Research Ethics for the Social Age

New Challenges, Cases, and Contexts
Author: Michael Zimmer,Katharina Kinder-Kurlanda
Publisher: Peter Lang Incorporated, International Academic Publishers
ISBN: 9781433142666
Category: Internet research
Page: 346
View: 6451

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Internet Research Ethics for the Social Age: New Challenges, Cases, and Contexts directly engages with the discussions and debates surrounding the Internet, and stimulates new ways to think about - and work towards resolving - the novel ethical dilemmas we face as internet and social media-based research continues to evolve.

Exploring the Boundaries of Big Data


Author: Bart van der Sloot,Dennis Broeders,Erik Schrijvers
Publisher: WRR Verkenningen
ISBN: 9789462983588
Category: Big data
Page: 286
View: 9061

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Though the exact nature and delineation of Big Data is still unclear, it seems likely that Big Data will have an enormous impact on our daily lives. 'Exploring the Boundaries of Big Data' serves as preparatory work for The Netherlands Scientific Council for Government Policy's advice to the Dutch government, which has asked the Council to address questions regarding Big Data, security and privacy. It is divided into five parts, each part engaging with a different perspective on Big Data: the technical, empirical, legal, regulatory and international perspective.

Conducting Research in Conservation

Social Science Methods and Practice
Author: Helen Newing
Publisher: Routledge
ISBN: 1136934391
Category: Science
Page: 400
View: 5857

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Conducting Research in Conservation is the first textbook on social science research methods written specifically for use in the expanding and increasingly multidisciplinary field of environmental conservation. The first section on planning a research project includes chapters on the need for social science research in conservation, defining a research topic, methodology, and sampling. Section two focuses on practical issues in carrying out fieldwork with local communities, from fieldwork preparation and data collection to the relationships between the researcher and the study community. Section three provides an in-depth focus on a range of social science methods including standard qualitative and quantitative methods such as participant observation, interviewing and questionnaires, and more advanced methods, such as ethnobiological methods for documenting local environmental knowledge and change, and participatory methods such as the ‘PRA’ toolbox. Section four then demonstrates how to analyze social science data qualitatively and quantitatively; and the final section outlines the writing-up process and what should happen after the end of the formal research project. This book is a comprehensive and accessible guide to social science research methods for students of conservation related subjects and practitioners trained in the natural sciences. It features practical worldwide examples of conservation-related research in different ecosystems such as forests; grasslands; marine and riverine systems; and farmland. Boxes provide definitions of key terms, practical tips, and brief narratives from students and practitioners describe the practical issues that they have faced in the field.

Big Data, Mining, and Analytics

Components of Strategic Decision Making
Author: Stephan Kudyba
Publisher: CRC Press
ISBN: 1466568712
Category: Computers
Page: 325
View: 5181

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There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making. Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments. It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining. Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics Introduces text mining and the transforming of unstructured data into useful information Examines real time wireless medical data acquisition for today’s healthcare and data mining challenges Presents the contributions of big data experts from academia and industry, including SAS Highlights the most exciting emerging technologies for big data—Hadoop is just the beginning Filled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analyzing unstructured data with text mining methods to supply you with the well-rounded understanding required to leverage your information assets into improved strategic decision making.

Research Methods for Business and Social Science Students


Author: John Adams,Hafiz T. A. Khan,Robert Raeside
Publisher: SAGE Publications India
ISBN: 8132119819
Category: Business & Economics
Page: 304
View: 5825

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Research Methods for Business and Social Science Students aims to present a clear discussion of the research methods employed in various disciplines related to our daily life problems. The theoretical basis of research methods is explained clearly and succinctly. Collecting data is a key part of the book and this includes both qualitative and quantitative methods of data collection, along with the advantages and disadvantages of each method. The book also describes in clear terms how students can analyse data, interpret results and link these to the literature review and hence their own contribution. It sets out a range of fundamental ideas in research methods, such as deductivism and inductivism, and explains why methodology is not the same as method. In this second edition every chapter has been re-written to be more readable and also to include more examples. The authors have also added a real student research proposal and a multiple-choice test with answers for the readers to test their own understanding of the ideas in the book. The book has been designed to illustrate research tools in a clear and accessible manner through chapters on such topics as formulating research, research design, data analysis and writing up the research results.