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Peer review of “Critical questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon” by boyd and Crawford 2012

Summary of the article

boyd and Crawford raises six provocations for Big Data. Instead of defining Big Data in terms of volume they define Big Data as a cultural, technological and scholarly phenomenon, which involves both technology, analysis and mythology. They argue it is time to critically examine the assumptions and biases of the Big Data phenomenon and this is the aim of the provocations they put forward, which are:

  • Big Data changes the definition of knowledge
  • Claims to objectivity and accuracy are misleading
  • Bigger data are not always better data
  • Taken out of context, Big Data loses its meaning
  • Just because it is accessible does not make it ethical
  • Limited access to Big Data creates new digital divides

3 Points of critique

  1. The article is called “Critical questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon”. The title is not that precise, as the provocations are not stated as questions in the article. A more accurate title could for instance be “Six provocations for Big Data”.
  1. There is a difference between the first sentence in the abstract and the first sentence in the article, which appear odd. The era of Big Data has begun. Vs. The era of Big Data is underway. This leaves the reader confused. Has the era begun or is it underway? Choose one of them.
  1. The article starts out with two quotes, but the section below does not refer back to them or elaborate why they are important. Neither are they mentioned in the rest of the paper. I recommend using the quotes actively by commenting on them or deleting them.

“Technology is neither good nor bad; nor is it neutral . . . technology’s inter- action with the social ecology is such that technical developments frequently have environmental, social, and human consequences that go far beyond the immediate purposes of the technical devices and practices themselves”. (Kranzberg 1986, p. 545)
We need to open a discourse – where there is no effective discourse now – about the varying temporalities, spatialities and materialities that we might represent in our databases, with a view to designing for maximum flexibility and allowing as possible for an emergent polyphony and polychrony. Raw data is both an oxymoron and a bad idea; to the contrary, data should be cooked with care”. (Bowker 2005, pp. 183–184)

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