Digital tools can help simplify qualitative researchers’ work. They can also add depth and richness by capturing data in a way that can be viewed and reviewed without preliminary transcription. This chapter shares an approach to working with digital data that honors participant voice and the lived experiences of those under study. The chapter also suggests new tools and common software applications. Further, it suggests a workflow to guide researchers as he or she begins to work to incorporate digital data into their studies.
TopBackground
In 2005 we wrote “Qualitative researchers have been attempting to make sense of the world around them since armchair anthropologists and sociologists left the confines of their familiar environments and ventured into the field (Crichton & Child, 2005; Crichton, 1997). Little has changed about the nature of the work and the challenges of working in the field. What have changed are the rapid development of digital tools and the increased availability of rich digital sources of data.
Typically, qualitative research, in particular ethnography and case study attempt “to construct in-depth depictions of the everyday life events of people through active re-searcher participation and engagement” (Crichton & Kinash, 2003, p. 102). Therefore, the biggest challenges of the work is managing the sheer quantity of data captured and the need to develop an elastic yet rigorous structure in which to organize and analyze it. Further, this management structure has to be nimble enough to allow the researcher to “read” and “re-read” the data, and organize and share it in a way that is accessible and ethical. The researcher has the added challenge of representing and maintaining the integrity of the firsthand experiences, in a narrative form that allows a reader, not familiar with the field, to gain insight and make personal sense from the rich description. As Genzuk (2004, p. 10) notes, it is through the narrative that “readers … understand fully the research setting and the thoughts of the people represented . . . [stopping] short, however, of becoming trivial and mundane” (Genzuk, 2004, p. 10).
With a bounty of rich digital data, the researcher is challenged to determine the balance between the essential description required to set the context and the critical analysis and interpretation that is necessary to help the reader come to an understanding of the findings. When that balance is achieved, the reader is able to interpret and understand the work and make relevant links that might extend the work and generalize the findings.