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Open Data, Big Data, and Just Data

In: Toward Information Justice

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  • Jeffrey Alan Johnson

    (Utah Valley University)

Abstract

This chapter examines two cases in which data presents questions of justice. Many argue as a philosophical principle that data sources should be available as widely as possible, the principle at the heart of the open data movement. But as I argue in that chapter, open data can just as easily lead to injustice: Like programming, “Injustice in, injustice out” ought to be a principle of data. Social privilege can color the data that is opened and create serious inequalities in who can access and use ostensibly open data. Open data can also establish standards that exclude knowledge that is not part of the data system. In the second case, I consider what big data means for higher education. After discussing some recent examples, I identify two types of ethical challenges in the increasingly common use of predictive analytics at universities: challenges related to the direct consequences of the systems and those rooted in the ideology of scientism that inspire them. Both the open data and big data cases prove quite problematic if the aim is just data.

Suggested Citation

  • Jeffrey Alan Johnson, 2018. "Open Data, Big Data, and Just Data," Public Administration and Information Technology, in: Toward Information Justice, chapter 0, pages 23-49, Springer.
    • Handle: RePEc:spr:paitcp:978-3-319-70894-2_2
    DOI: 10.1007/978-3-319-70894-2_2
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