Mind mapping in qualitative data analysis: Managing interview data in interdisciplinary and multi-sited research projects

Abstract

Typically, interviews are transcribed to enable coding and analysis of the data to establish the research findings. However, where discourse is not central, this article argues that mind mapping is a valuable tool to identify relationships and differences across large datasets. This is particularly useful for large-scale research projects that may also be interdisciplinary and/or multi-sited where the ability to transcribe and analyse audio-recordings is often a time-intensive process for the researcher and costly if outsourced. Additionally, there are challenges to analysing vast amounts of text into something meaningful. This article first reviews what mind maps are, and how they work. Second it explores the value of mind maps in qualitative data collection and analysis, particularly in the role of transcription. Third, using research conducted on volcano alert level systems, a methodology using mind maps to analyse interview recording is established. Fourth, the pros and cons of mind maps and potential application in other qualitative research methods and in different academic fields is discussed. Findings demonstrate that mind maps can be highly time beneficial providing a close and intimate reading of the data and enabling the researcher to make sense of the emerging themes, particularly for large data sets typically collected through multi-sited research, or smaller research projects with limited resources.