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Encyclopedia of Big Data

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Encyclopedia of Big Data/ edited by Laurie A. Schintler, Connie L. McNeely.
其他作者:	McNeely, Connie L.
面頁冊數:	online resource. :
Contained By:	Springer Nature Living Reference
標題:	Statistical Theory and Methods. -
電子資源:	https://doi.org/10.1007/978-3-319-32001-4
ISBN:	9783319320014

Encyclopedia of Big Data
Encyclopedia of Big Data[electronic resource] /edited by Laurie A. Schintler, Connie L. McNeely. - online resource.

Advertising Targeting -- Algorithm -- Algorithmic Accountability -- American Bar Association -- American Civil Liberties Union -- American Library Association -- Animals -- Anonymity -- Anonymization techniques -- Anthropology -- Apple -- Archaeology -- Arts -- Asian Americans Advancing Justice -- Association vs. Causation -- Astronomy -- Automated Modeling/Decision Making -- Behavioral Analytics -- Belgium -- Big Data Business Model Maturity Index -- Big Data Storytelling, Digital Storytelling -- Big Humanities Project -- Big Variety Data -- Bioinformatics -- Biomedical Data -- Biometrics -- Biosurveillance -- Blogs -- Brand Monitoring -- Business-to-Business (B2B) -- Business-to-Community (B2C) -- Cancer -- Cell Phone Data -- Center for National Security Studies -- Charter of Fundamental Rights (EU) -- Clickstream Analytics -- Cloud Services -- Common Sense Media -- Communications -- Complex Networks -- Computational Social Sciences -- Computer Science -- Content Management System (CMS) -- Content Moderation -- Correlation vs. Causation -- Criminology and Law Enforcement -- Crowdsourcing -- Cultural Analytics -- Curriculum, Higher Education, Humanities -- Curriculum, Higher Education, Social sciences -- Cyber Espionage -- Cyber Threats/Attacks -- Cybersecurity -- Data Integration -- Data Mining -- Data Model, Data Modeling -- Data Monetization -- Data Provenance -- Data Repository -- Data Science -- Data Scientist -- Data Visualization -- Data-Driven Marketing -- Data-Information-Knowledge-Action Model -- Decision Theory -- Decision Tree -- Demographic Data -- Digital Advertising Alliance -- Digital Divide -- Digital Knowledge Network Divide -- Digital Libraries -- Digital Literacy -- Digitization -- Discovery Analytics -- Diversity -- Drones -- Drug Enforcement Administration -- e-commerce -- Economics -- Education -- Education and Training -- Electronic Health Records (EHR) -- Energy -- Entertainment -- Environment -- Epidemeology -- European Commission -- European Commission: Directorate-General for Justice (Data Protection Division) -- European Union -- European Union Data Protection Supervisor -- Evidence-Based Medicine -- Facebook -- Facial Recognition Technologies -- Federal Bureau of Investigation (FBI) -- Financial Data and Trend Prediction -- Financial Services -- Fourth Amendment -- France -- Future of Privacy -- Gender and Sexuality -- Genealogy -- Geography -- Germany -- Google -- Google Analytics -- Google Flu -- Governance -- Health Care Delivery -- Health Informatics -- HIPAA -- Human Resources Management -- Humanities (Digital Humanities) -- Industrial and Commercial Bank of China -- Information Commissioner, United Kingdom -- Information Society -- Interactive Data Visualization -- International Development -- International Labor Organization -- International Nongovernmental Organizations (INGOs) -- Internet -- Internet Association, The -- Internet of Things -- Italy -- Journalism -- Keystroke Capture -- Knowledge Management -- LexisNexis -- Link Prediction -- Link/Graph Mining -- LinkedIn -- Marketing/Advertising -- Mathematics -- Media -- Medicaid -- Metadata -- Military Operations, Counter-Intelligence -- Military Operations, Counter-Terrorism -- Mobile Analytics -- National Association for the Advancement of Colored People -- National Geospatial-Intelligence Agency -- National Oceanic and Atmospheric Administration -- National Organization for Women -- National Security Administration (NSA) -- Netflix -- Netherlands -- Network Advertising Initiative -- Network Analytics -- Neural Networks -- Neuroscience -- NoSQL (Not Structured Query Language) -- Nutrition -- Online Advertising -- Online Identity -- Ontologies -- Open Data -- Open Society Foundations -- Open-Source Software -- Organiztion of American States -- Participatory Health -- Patient Records -- Patient-Centered (Personalized) Health -- PatientsLikeMe -- Pharmaceutical Industry -- Physics -- Policy Analysis -- Political Science -- Pollution, Air -- Pollution, Land -- Pollution, Water -- Predictive Analytics -- Prevention -- Privacy -- Psychology -- Regression -- Religion -- Risk Analysis -- Robinson & Yu LLC -- R-Programming -- SalesForce -- Scientometrics -- Semantic Web -- Semantic/Content Analysis/Natural Language Process -- Semi-Structured Data -- Sentiment Analysis -- Smart Cities -- Social Media -- Social Network Analysis (SNA) -- Social Sciences -- Sociology -- South Korea -- Spain -- Spatial Data -- Storage -- Supercomputing, Exascale Computing, High Performance Computing -- Supreme Court -- Tableau Software -- Telemedicine -- Text Analytics -- Transparency -- Treatment -- United Nations Educational, Scientific and Cultural Organization (UNESCO) -- Visualization -- Volunteered Geographic Information (VGI) -- White House Big Data Initiative -- White House Brain Initiative -- Wikileaks -- Wikipedia -- Workforce -- World Bank -- Zappos -- Zillow.

This encyclopedia will be an essential resource for our times, reflecting the fact that we currently are living in an expanding data-driven world. Technological advancements and other related trends are contributing to the production of an astoundingly large and exponentially increasing collection of data and information, referred to in popular vernacular as “Big Data.” Social media and crowdsourcing platforms and various applications ― “apps” ― are producing reams of information from the instantaneous transactions and input of millions and millions of people around the globe. The Internet-of-Things (IoT), which is expected to comprise tens of billions of objects by the end of this decade, is actively sensing real-time intelligence on nearly every aspect of our lives and environment. The Global Positioning System (GPS) and other location-aware technologies are producing data that is specific down to particular latitude and longitude coordinates and seconds of the day. Large-scale instruments, such as the Large Hadron Collider (LHC), are collecting massive amounts of data on our planet and even distant corners of the visible universe. Digitization is being used to convert large collections of documents from print to digital format, giving rise to large archives of unstructured data. Innovations in technology, in the areas of Cloud and molecular computing, Artificial Intelligence/Machine Learning, and Natural Language Processing (NLP), to name only a few, also are greatly expanding our capacity to store, manage, and process Big Data. In this context, the Encyclopedia of Big Data is being offered in recognition of a world that is rapidly moving from gigabytes to terabytes to petabytes and beyond. While indeed large data sets have long been around and in use in a variety of fields, the era of Big Data in which we now live departs from the past in a number of key respects and with this departure comes a fresh set of challenges and opportunities that cut across and affect multiple sectors and disciplines, and the public at large. With expanded analytical capacities at hand, Big Data is now being used for scientific inquiry and experimentation in nearly every (if not all) disciplines, from the social sciences to the humanities to the natural sciences, and more. Moreover, the use of Big Data has been well established beyond the Ivory Tower. In today’s economy, businesses simply cannot be competitive without engaging Big Data in one way or another in support of operations, management, planning, or simply basic hiring decisions. In all levels of government, Big Data is being used to engage citizens and to guide policy making in pursuit of the interests of the public and society in general. Moreover, the changing nature of Big Data also raises new issues and concerns related to, for example, privacy, liability, security, access, and even the veracity of the data itself. Given the complex issues attending Big Data, there is a real need for a reference book that covers the subject from a multi-disciplinary, cross-sectoral, comprehensive, and international perspective. The Encyclopedia of Big Data will address this need and will be the first of such reference books to do so. Featuring some 500 entries, from "Access" to "Zillow," the Encyclopedia will serve as a fundamental resource for researchers and students, for decision makers and leaders, and for business analysts and purveyors. Developed for those in academia, industry, and government, and others with a general interest in Big Data, the encyclopedia will be aimed especially at those involved in its collection, analysis, and use. Ultimately, the Encyclopedia of Big Data will provide a common platform and language covering the breadth and depth of the topic for different segments, sectors, and disciplines. .

ISBN: 9783319320014

Standard No.: 10.1007/978-3-319-32001-4doiSubjects--Topical Terms:

671396
Statistical Theory and Methods.

LC Class. No.: HF5548.125-5548.6

Dewey Class. No.: 658.4038

Encyclopedia of Big Data
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520 $a This encyclopedia will be an essential resource for our times, reflecting the fact that we currently are living in an expanding data-driven world. Technological advancements and other related trends are contributing to the production of an astoundingly large and exponentially increasing collection of data and information, referred to in popular vernacular as “Big Data.” Social media and crowdsourcing platforms and various applications ― “apps” ― are producing reams of information from the instantaneous transactions and input of millions and millions of people around the globe. The Internet-of-Things (IoT), which is expected to comprise tens of billions of objects by the end of this decade, is actively sensing real-time intelligence on nearly every aspect of our lives and environment. The Global Positioning System (GPS) and other location-aware technologies are producing data that is specific down to particular latitude and longitude coordinates and seconds of the day. Large-scale instruments, such as the Large Hadron Collider (LHC), are collecting massive amounts of data on our planet and even distant corners of the visible universe. Digitization is being used to convert large collections of documents from print to digital format, giving rise to large archives of unstructured data. Innovations in technology, in the areas of Cloud and molecular computing, Artificial Intelligence/Machine Learning, and Natural Language Processing (NLP), to name only a few, also are greatly expanding our capacity to store, manage, and process Big Data. In this context, the Encyclopedia of Big Data is being offered in recognition of a world that is rapidly moving from gigabytes to terabytes to petabytes and beyond. While indeed large data sets have long been around and in use in a variety of fields, the era of Big Data in which we now live departs from the past in a number of key respects and with this departure comes a fresh set of challenges and opportunities that cut across and affect multiple sectors and disciplines, and the public at large. With expanded analytical capacities at hand, Big Data is now being used for scientific inquiry and experimentation in nearly every (if not all) disciplines, from the social sciences to the humanities to the natural sciences, and more. Moreover, the use of Big Data has been well established beyond the Ivory Tower. In today’s economy, businesses simply cannot be competitive without engaging Big Data in one way or another in support of operations, management, planning, or simply basic hiring decisions. In all levels of government, Big Data is being used to engage citizens and to guide policy making in pursuit of the interests of the public and society in general. Moreover, the changing nature of Big Data also raises new issues and concerns related to, for example, privacy, liability, security, access, and even the veracity of the data itself. Given the complex issues attending Big Data, there is a real need for a reference book that covers the subject from a multi-disciplinary, cross-sectoral, comprehensive, and international perspective. The Encyclopedia of Big Data will address this need and will be the first of such reference books to do so. Featuring some 500 entries, from "Access" to "Zillow," the Encyclopedia will serve as a fundamental resource for researchers and students, for decision makers and leaders, and for business analysts and purveyors. Developed for those in academia, industry, and government, and others with a general interest in Big Data, the encyclopedia will be aimed especially at those involved in its collection, analysis, and use. Ultimately, the Encyclopedia of Big Data will provide a common platform and language covering the breadth and depth of the topic for different segments, sectors, and disciplines. .
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