Big Data, Little Data, No Data Scholarship in the Networked World

"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...

Celý popis

Uložené v:
Podrobná bibliografia
Hlavný autor: Borgman, Christine L
Médium: E-kniha Kniha
Jazyk:English
Vydavateľské údaje: Cambridge, Mass MIT Press 2015
The MIT Press
Vydanie:1
Predmet:
Big data
Communication in learning and scholarship
Communication in learning and scholarship > Technological innovations
Computing and Processing
Cyberinfrastructure
Data processing
General Topics for Engineers
Information Science
Information storage and retrieval systems
Information technology
Internet Studies
Library Science
Methodology
Research > Data processing
Research > Methodology
Technological innovations
Technology
Technology & Policy
ISBN:0262028565, 9780262028561, 9780262529914, 0262529912, 9780262327862, 0262327864
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Obsah:
  • Front Matter Table of Contents Detailed Table of Contents Preface Acknowledgments 1: Provocations 2: What Are Data? 3: Data Scholarship 4: Data Diversity [II Introduction] 5: Data Scholarship in the Sciences 6: Data Scholarship in the Social Sciences 7: Data Scholarship in the Humanities 8: Sharing, Releasing, and Reusing Data 9: Credit, Attribution, and Discovery of Data 10: What to Keep and Why References Index
  • Intro -- Contents -- Detailed Table of Contents -- Preface -- Acknowledgments -- I Data and Scholarship -- 1 Provocations -- 2 What Are Data? -- 3 Data Scholarship -- 4 Data Diversity -- II Case Studies in Data Scholarship -- 5 Data Scholarship in the Sciences -- 6 Data Scholarship in the Social Sciences -- 7 Data Scholarship in the Humanities -- III Data Policy and Practice -- 8 Sharing, Releasing, and Reusing Data -- 9 Credit, Attribution, and Discovery of Data -- 10 What to Keep and Why -- References -- Index