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Accessibility and Flexibility: Two Organizing Principles for Big Data Collaboration

  • Libby Hemphill
  • Susan T. Jackson
Chapter
Part of the Computational Social Sciences book series (CSS)

Abstract

The chapter argues that accessibility and flexibility are the two principles and practices that can bring big data projects the closest to a data factory ideal. The chapter elaborates on the necessity of these two principles, offering a reasoned explanation for their value in context. Using two big data social scientific research projects as a springboard for conversation the chapter highlights both the advantages and the practical limits within which accessibility and flexibility operate. The authors avoid both utopian and dystopian tropes about big data approaches. In addition, they offer a critical feminist discussion of big data collaboration. Of particular interest are also the manner in which specific characteristics of big data projects, especially volume and velocity, may affect multidisciplinary collaborations.

Keywords

Data management Data access Data collection Feminism Big data 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of MichiganAnn ArborUSA
  2. 2.Stockholm UniversityStockholmSweden

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