Publication

Approaches to Building Big Data Literacy

D’Ignazio, C., & Bhargava, R. (2015). Approaches to Building Big Data Literacy. In Bloomberg Data for Good Exchange 2015. New York, NY, USA.

Abstract

Big Data projects are being rapidly embraced by organizations working in the social good sector. This has led to a proliferation of new projects, with strong criticisms in response focusing on the disempowering aspects of these projects. This paper identifies four main problematic aspects of Big Data projects in the social good sector to focus on: lack of transparency, extractive collection, technological complexity, and control of impact. Leveraging Paulo Freire’s concept of "Popular Education", we identify an opportunity to work on these issues in empowering ways through literacy education. We discuss existing definitions of data literacy and find a need to create an extended definition of Big Data literacy. Surveying existing approaches to building data literacy, we identify the need for new approaches and technologies to ad- dress the problematic aspects of Big Data projects. To flesh out this concept of "Popular Big Data", we close by o er- ing seven ideas for how the field can ensure that Big Data projects are in line with the values of organizations working in the social good sector.

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