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.
Highlights
Data sets from qualitative studies increasingly are stored in digital archives and available for reuse, notably in the UK and more widely (Corti 2017)
‘Why would you want to do that?’ is a comment we have received more than once from audiences of qualitative researchers when presenting our ideas about the feasibility of conducting secondary analysis across existing multiple small-scale archived qualitative longitudinal studies
In the rest of the paper we demonstrate a breadth-and-depth method for how qualitative researchers can work with ‘big qual’ data 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
Summary
Data sets from qualitative studies increasingly are stored in digital archives and available for reuse, notably in the UK and more widely (Corti 2017). Mason identified the need for: ‘appropriately qualitative ways to “scale up” research resources currently generated through multiple small-scale studies, to fully exploit the massive potential that qualitative research offers for making crosscontextual generalisations’ (ibid: 3—our emphasis). This search for qualitative ways of dealing with large amounts of secondary data remains a challenge. ‘Why would you want to do that?’ is a comment we have received more than once from audiences of qualitative researchers when presenting our ideas about the feasibility of conducting secondary analysis across existing multiple small-scale archived qualitative longitudinal studies. In the rest of the paper we demonstrate a breadth-and-depth method for how qualitative researchers can work with ‘big qual’ data 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
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