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Big Data Factories : Collaborative Approaches /

The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as data factoring emphasizes the need to think of each individual dataset developed by an individual project as p...

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Bibliographic Details
Corporate Authors: SpringerLink Online service
Group Author: Matei, Sorin A. Sorin Adam, 1965; Jullien, Nicolas; Goggins, Sean P
Published: Springer International Publishing : Imprint: Springer,
Publisher Address: Cham :
Publication Dates: 2017.
Literature type: eBook
Language: English
Series: Computational Social Sciences,
Subjects:
Computer science
Big data
Research > Moral and ethical aspects
Data mining
Application software
Bioinformatics
Data Mining and Knowledge Discovery
Big Data/Analytics
Computer Appl. in Social and Behavioral Sciences
Research Ethics
Online Access: http://dx.doi.org/10.1007/978-3-319-59186-5
Summary: The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as data factoring emphasizes the need to think of each individual dataset developed by an individual project as part of a broader data ecosystem, easily accessible and exploitable by parties not directly involved with data collection and documentation. Furthermore, data factoring uses and encourages pre-analytic operations that add value to big data sets, especially recombining and repurposing. The book prop
Carrier Form: 1 online resource(VI,141pages): illustrations.
ISBN: 9783319591865
Index Number: QA76
CLC: TP311.13
Contents: Chapter1. Introduction -- Part 1: Theoretical Principles and Approaches to Data Factories -- Chapter2. Accessibility and Flexibility: Two Organizing Principles for Big Data Collaboration -- Chapter3. The Open Community Data Exchange: Advancing Data Sharing and Discovery in Open Online Community Science -- Part 2: Theoretical principles and ideas for designing and deploying data factory approaches -- Chapter4. Levels of Trace Data for Social and Behavioral Science Research -- Chapter5. The 10 Adoption Drivers of Open Source Software that Enables e-Research in Data Factories for Open Innovatio

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