Peer Review of Critical Question for Big Data

I am writing this peer review on the article “Critical Questions for Big Data” by Boyd D. & Crawford K. (2012).

The writers want to start a discussion about Big Data but fall short at being trustworthy or credible, as they only include one side of the matter. I know this article has been written to ask critical questions about Big Data but hear me out.

To start with I would like to compliment the writers on the easy and clear overview of points that are going to be covered, using headlines. This together with the language being clear makes it very easy and enjoyable to read. On page 663, the writers list how they define Big Data and I must comment on how well this communicates their definition and perspective of Big Data.

This said the overuse of semi-colon in this article and the use of dashes to inject side notes have the tendency to put the reader out of their reading momentum. Here is an example:

“Data sets that were once obscure and difficult to manage — and, thus, only of interest to social scientists — are now being aggregated and made …” (Crawford B., 2012, p. 664)

Instead, they could try and trim these away — or, if necessary, rearrange the sentences. By only including the downsides and misunderstandings of Big Data, the writers unintentionally put the reader into one of two camps. Those provoked by this article and for Big Data and those agreeing on the points that the article makes. Instead of this, I would suggest putting out pros and cons for different aspect and examples of quotes from other authors.

The writer even mentions these different opinions in the start but never gets back to the positive ones. By including these, it would start a discussion or conversation that allowed for a lot more diversity in opinion, than just painting Big Data as being a bad thing. Here are some examples:

1) Their choice of words has a lot of loaded sentiment in them and has the effect of favor one opinion over the other. Already in the introduction, using words as “clamoring”. “…, and other scholars are clamoring for access to the massive quantities of information …” (p. 663). Instead, using a more neutral language would put the writer in a more objective position and thereby become more trustworthy. Even the writers themselves state this fact “Subjectivity, on the other hand, is viewed with suspicion, colored …” (p. 667), which just makes the writers hypocrites.

2) In the second segment of the article, they point out that Big Data is affected by the researchers’ subjectivity and I couldn’t agree more, but that is beside the case. Throughout the article, the writers state something without taking advantage of available material that could back them up or, going back to the previous point, even challenge their perspectives. When talking about objectivity and data, it should be given to bring up feminism theory, situatedness and maybe even refer to articles by Haraway, Suchman or even Fujimura “… working with Big Data is still subjective, and what it quantifies does not necessarily have a closer claim on objective truth …” (p. 667). These materials would not only give the writers more credibility but would also create a more nuanced debate. Feminism theory specifically speaks about acknowledging the situatedness the people, in contact with data, may be affected by.

3) In the third segment, the writers neglect to take advantage of materials. They state that either you use Big Data or “Small Data”. Bring up “Big data needs thick data” by Wang, T. (2013). She argues that quantitative data is not enough by itself, Big data by itself needs information to reveal the knowledge gaps. Again, this would have started a more nuanced discussion challenging viewpoints and created a more critical view on the topic at hand.

Overall, a good read but I’d like to see a piece that is more open to diverse arguments and uses these to reflect on and further discuss the element in focus.

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