Big Data Factories

Big Data Factories

Collaborative Approaches

Jullien, Nicolas; Matei, Sorin Adam; Goggins, Sean P.

Springer International Publishing AG

08/2018

141

Mole

Inglês

9783319865645

15 a 20 dias

454

Descrição não disponível.
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.
trends in data collection;data recombination and reuse;creating collaborative spaces;fungible big data sets;factoring data;alphabet of social interaction;networks of online interaction;large scale data privacy and security;research ethics