The challenge of “Big Data”: What does it mean for the qualitative research industry?

Abstract

There is something very appealing about "data" that convince us that they somehow have an omniscient quality. Data that are generated with the apparent lack of human intervention have an even more magical quality that deters us from questioning them. This mythology around data has been noted by Boyd and Crawford (2012) who considered that there is a:[…] widespread belief that large data sets offer a higher form of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity, and accuracy.Of course, we are all now aware that we are living in the "Big Data" era. "Big" plays an important part in the discourse around data, not least because of the ready supply of statistics concerning the scale of data in today's world. Martin Hilbert of the University of Southern California (Hilbert and López, 2011;Hilbert and López, 2012) has attempted to put a number on this growth, estimating that in 2007 the total volume of stored data were 300 exabytes. By 2013, with digital data doubling every three years, he estimates that the amount of stored information in the world now stands at 1,200 exabytes.The scale of Big Data lends itself to highly visual means of description, as described by Mayer-Schönberger and Cukier (2013):

Sacred Excess: Organizational Ignorance in an Age of Toxic Data

“…Colin Strong of the research firm GfK Technology warned that the mythological promises of data might make researchers less inclined to critically question their magical and auratic properties: ‘There is something very appealing about “data” that convince us that they somehow have an omniscient quality. Data that are generated with the apparent lack of human intervention have an even more magical quality that deters us from questioning them’ (Strong, 2014, p. 336). In a widely cited article by Danah Boyd and Kate Crawford, both associated with Microsoft’s think tank Microsoft Research, readers are warned against the ‘widespread belief that large data sets offer a higher form of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity and accuracy’ (Boyd & Crawford, 2012).…”

What are the threats and potentials of big data for qualitative research?

“…Something is lost when the complexities of human reasoning are datified or determined by the data scientists. Strong (2013: 340) cautions: There is a danger that the avalanche of digital data about our lives is used in a way that underestimates the nature of the human condition . .…”

“…Qualitative researchers are well-positioned to generate research questions, and to select, curate, interpret and theorize big data away from reductionist claims (Strong, 2013). Bail (2014: 467) sees that the slow uptake of big data in fields such as cultural sociology is astounding:…”

“…Qualitative researchers are well-positioned to generate research questions, and to select, curate, interpret and theorize big data away from reductionist claims (Strong, 2013). Bail (2014: 467) sees that the slow uptake of big data in fields such as cultural sociology is astounding: inattention to big data among cultural sociologists is doubly surprising since it is naturally occurring – unlike survey research or cross-sectional qualitative interviews – and therefore critical to understanding the evolution of meaning structures in situ .…”

“…Within the academic community, some have argued that big data renders small-scale research, commonly used in the social sciences and humanities, potentially at risk (Alberts, 2012; Berlekamp, 2012; Meyer, 2009). If social and behavioral data, that were previously the locus of much qualitative research have been ‘datified’, is the role of the qualitative researcher losing a significant foothold (Strong, 2013). This article argues that before researchers blindly follow the big data trends, questions need to be asked about the accessibility, ethics, and utility of big data.…”