LEADER 06924nam 2200733 450 001 9910136883303321 005 20231222065013.0 010 $a1-119-13842-6 010 $a1-119-13841-8 035 $a(CKB)3710000000657745 035 $a(EBL)4519004 035 $a(SSID)ssj0001668911 035 $a(PQKBManifestationID)16460567 035 $a(PQKBTitleCode)TC0001668911 035 $a(PQKBWorkID)14910377 035 $a(PQKB)11258843 035 $a(PQKBManifestationID)16332941 035 $a(PQKBWorkID)14910607 035 $a(PQKB)20718305 035 $a(DLC) 2016006245 035 $a(Au-PeEL)EBL4519004 035 $a(CaPaEBR)ebr11206427 035 $a(CaONFJC)MIL921109 035 $a(OCoLC)937999328 035 $a(CaSebORM)9781119138402 035 $a(MiAaPQ)EBC4519004 035 $a(EXLCZ)993710000000657745 100 $a20160518h20162016 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe data industry $ethe business and economics of information and big data /$fChunlei Tang 205 $a1st edition 210 1$aHoboken, New Jersey :$cWiley,$d2016. 210 4$dİ2016 215 $a1 online resource (218 p.) 225 1 $aTHEi Wiley ebooks 300 $aDescription based upon print version of record. 311 $a1-119-13843-4 311 $a1-119-13840-X 320 $aIncludes bibliographical references and index. 327 $acover; Title Page; Copyright; Dedication; Contents; Preface; Chapter 1 What is Data Industry?; 1.1 Data; 1.1.1 Data Resources; 1.1.2 The Data Asset; 1.2 Industry; 1.2.1 Industry Classification; 1.2.2 The Modern Industrial System; 1.3 Data Industry; 1.3.1 Definitions; 1.3.2 An Industry Structure Study; 1.3.3 Industrial Behavior; 1.3.4 Market Performance; Chapter 2 Data Resources; 2.1 Scientific Data; 2.1.1 Data-Intensive Discovery in the Natural Sciences; 2.1.2 The Social Sciences Revolution; 2.1.3 The Underused Scientific Record; 2.2 Administrative Data; 2.2.1 Open Governmental Affairs Data 327 $a2.2.2 Public Release of Administrative Data2.2.3 A ""Numerical"" Misunderstanding in Governmental Affairs; 2.3 Internet Data; 2.3.1 Cyberspace: Data of the Sole Existence; 2.3.2 Crawled Fortune; 2.3.3 Forum Opinion Mining; 2.3.4 Chat with Hidden Identities; 2.3.5 Email: The First Type of Electronic Evidence; 2.3.6 Evolution of the Blog; 2.3.7 Six Degrees Social Network; 2.4 Financial Data; 2.4.1 Twins on News and Financial Data; 2.4.2 The Annoyed Data Center; 2.5 Health Data; 2.5.1 Clinical Data: EMRs, EHRs, and PHRs; 2.5.2 Medicare Claims Data Fraud and Abuse Detection 327 $a2.6 Transportation Data2.6.1 Trajectory Data; 2.6.2 Fixed-Position Data; 2.6.3 Location-Based Data; 2.7 Transaction Data; 2.7.1 Receipts Data; 2.7.2 e-Commerce Data; Chapter 3 Data Industry Chain; 3.1 Industrial Chain Definition; 3.1.1 The Meaning and Characteristics; 3.1.2 Attribute-Based Categories; 3.2 Industrial Chain Structure; 3.2.1 Economic Entities; 3.2.2 Environmental Elements; 3.3 Industrial Chain Formation; 3.3.1 Value Analysis; 3.3.2 Dimensional Matching; 3.4 Evolution of Industrial Chain; 3.5 Industrial Chain Governance; 3.5.1 Governance Patterns; 3.5.2 Instruments of Governance 327 $a3.6 The Data Industry Chain and its Innovation Network3.6.1 Innovation Layers; 3.6.2 A Support System; Chapter 4 Existing Data Innovations; 4.1 Web Creations; 4.1.1 Network Writing; 4.1.2 Creative Designs; 4.1.3 Bespoke Style; 4.1.4 Crowdsourcing; 4.2 Data Marketing; 4.2.1 Market Positioning; 4.2.2 Business Insights; 4.2.3 Customer Evaluation; 4.3 Push Services; 4.3.1 Targeted Advertising; 4.3.2 Instant Broadcasting; 4.4 Price Comparison; 4.5 Disease Prevention; 4.5.1 Tracking Epidemics; 4.5.2 Whole-Genome Sequencing; Chapter 5 Data Services in Multiple Domains; 5.1 Scientific Data Services 327 $a5.1.1 Literature Retrieval Reform5.1.2 An Alternative Scholarly Communication Initiative; 5.1.3 Scientific Research Project Services; 5.2 Administrative Data Services; 5.2.1 Police Department; 5.2.2 Statistical Office; 5.2.3 Environmental Protection Agency; 5.3 Internet Data Services; 5.3.1 Open Source; 5.3.2 Privacy Services; 5.3.3 People Search; 5.4 Financial Data Services; 5.4.1 Describing Correlations; 5.4.2 Simulating Market-Makers' Behaviors; 5.4.3 Forecasting Security Prices; 5.5 Health Data Services; 5.5.1 Approaching the Healthcare Singularity; 5.5.2 New Drug of Launching Shortcuts 327 $a5.5.3 Monitoring in Chronic Disease 330 $aProvides an introduction of the data industry to the field of economics This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises? business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees. Defines and develops the concept of a ?Data Industry,? and explains the economics of data to data scientists and statisticians Includes numerous case studies and examples from a variety of industries and disciplines Serves as a useful guide for practitioners and entrepreneurs in the business of data technology The Data Industry: The Business and Economics of Information and Big Data is a resource for practitioners in the data science industry, government, and students in economics, business, and statistics. CHUNLEI TANG , Ph.D., is a research fellow at Harvard University. She is the co-founder of Fudan?s Institute for Data Industry and proposed the concept of the ?data industry?. She received a Ph.D. in Computer and Software Theory in 2012 and a Master of Software Engineering in 2006 from Fudan University, Shanghai, China. 410 0$aTHEi Wiley ebooks. 606 $aInformation technology$xEconomic aspects 606 $aBig data$xEconomic aspects 615 0$aInformation technology$xEconomic aspects. 615 0$aBig data$xEconomic aspects. 676 $a338.4/70057 700 $aTang$b Chunlei$0921316 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910136883303321 996 $aThe data industry$92066472 997 $aUNINA