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...
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| Other Authors: | , , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
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| Series: | Computational Social Sciences,
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| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of 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 Innovations
- Chapter6. Aligning online social collaboration data around social order: theoretical considerations and measures
- Part 3: Approaches in action through case studies of data based research, best practice scenarios, or educational briefs
- Chapter7. Lessons learned from a decade of FLOSS data collection
- Chapter8. Teaching Students How (NOT) to Lie, Manipulate, and Mislead with Information Visualizations
- Chapter9. Democratizing Data Science: The Community Data Science Workshops and Classes.
