Big data, little data, no data : scholarship in the networked world /

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An examination of the uses of data within a changing knowledge infrastructure, offering analysis and case studies from the sciences, social sciences, and humanities.

Bibliographic Details
Call Number:Libro Electrónico
Main Author: Borgman, Christine L., 1951- (Author)
Format: Electronic eBook
Language:Inglés
Published: Cambridge, Massachusetts : The MIT Press, [2015]
Subjects:
Communication in learning and scholarship > Technological innovations.
Research > Methodology.
Research > Data processing.
Information technology.
Information storage and retrieval systems.
Cyberinfrastructure.
Information resources management.
Research.
Research Design
Information Systems
Information Dissemination
Information Management
Research
Communication savante > Innovations.
Recherche > Méthodologie.
Technologie de l'information.
Systèmes d'information.
Gestion de l'information.
Recherche.
information technology.
research (function)
COMPUTERS > Computer Literacy.
COMPUTERS > Computer Science.
COMPUTERS > Data Processing.
COMPUTERS > Hardware > General.
COMPUTERS > Information Technology.
COMPUTERS > Machine Theory.
COMPUTERS > Reference.
LANGUAGE ARTS & DISCIPLINES > Library & Information Science > General.
Information resources management
Communication in learning and scholarship > Technological innovations
Cyberinfrastructure
Information storage and retrieval systems
Information technology
Research > Data processing
Research > Methodology
Datenstruktur
E-Science
Informationssystem
Wissenschaft
Vetenskaplig elektronisk publicering.
Forskningsmetodik.
Informationsteknik.
Informationssystem.
Store datamengder > Informasjonsteknologi > Datautvinning > Forskningsmetoder > Cyberspace
INFORMATION SCIENCE/Technology & Policy
INFORMATION SCIENCE/Internet Studies
INFORMATION SCIENCE/General
Electronic books.
Online Access:Texto completo
Table of Contents:
  • Provocations
  • What are data?
  • Data scholarship
  • Data diversity
  • Data scholarship in the sciences
  • Data scholarship in the social sciences
  • Data scholarship in the humanities
  • Sharing, releasing, and reusing data
  • Credit, attribution, and discovery of data
  • What to keep and why to keep them.

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