Big data, qualitative style: a breadth-and-depth method for working with large amounts of secondary qualitative data

Emma Davidson, Rosalind Edwards, Lynn Jamieson and Susie Weller ()
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Emma Davidson: University of Edinburgh
Rosalind Edwards: University of Southampton
Lynn Jamieson: University of Edinburgh
Susie Weller: University of Southampton

Quality & Quantity: International Journal of Methodology, 2019, vol. 53, issue 1, No 18, 363-376

Abstract: Abstract Archival storage of data sets from qualitative studies presents opportunities for combining small-scale data sets for reuse/secondary analysis. In this paper, we outline our approach to combining multiple qualitative data sets and explain why working with a corpus of ‘big qual’ data is a worthwhile endeavour. We present a new approach that iteratively combines recursive surface thematic mapping and in-depth interpretive work. Our breadth-and-depth method involves a series of steps: (1) surveying archived data sets to create a new assemblage of data; (2) recursive surface thematic mapping in dialogue with (3) preliminary ‘test pit’ analysis, remapping and repetition of preliminary analysis; and (4) in-depth analysis of the type that is familiar to most qualitative researchers. In so doing, we show how qualitative researchers can conduct ‘big qual’ analysis while retaining the distinctive order of knowledge about social processes that is the hallmark of rigorous qualitative research, with its integrity of attention to nuanced context and detail.

Keywords: Archived data; Big data; Big qual; Breadth-and-depth method; Qualitative analysis; Secondary analysis (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s11135-018-0757-y

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