Searching for accessible examples of creative analysis

In the ‘Creativity in Research’ webinar we delivered in 2021, we presented examples of our own creative research methods. We spoke about the ways in which we had found, unearthed, and stumbled towards or across approaches to doing data analysis creatively within the context of particular projects. Although we knew that many researchers were already doing data analysis creatively, we saw that some people were struggling for permission to do things differently as well as seeking to find formal writing on the subject. We were struck by a realisation that many were looking for usable examples of doing data analysis differently; for practical resources that they could pick up and apply; and for texts that could describe, simply, how creative approaches have been undertaken and to what effect epistemologically, methodologically, and substantively.

This search for formal writing on the subject reflects an appetite for learning from others and we are confident that creative methods of analysis will become central to new developments in research in the coming years, not least because the move towards transdisciplinary research requires the kinds of development, adaptation, and mixing of methods found in this book. The idea of being engaged in a search also captures something of our intent as editors of this collection. We recognise that we need this handbook as surely as those who attended the webinar and many of those who have contributed chapters have told us that they need this handbook too.

One directive we gave to all authors in preparing their chapters was to outline a case example of a method of analysis in enough detail for another researcher to be able to use their approach. The authors all made serious attempts to deliver on this request and each chapter provides some form of ‘map’ of the journey taken. Ingold (2011, p 204) argues that maps are often more useful in ‘revealing the inner reality of the world’ than providing some coherent view of its ‘outer surface’. We believe that that the chapters in this collection do both and we see how researchers have had to struggle to find an approach that they can live with themselves, but which will also be seen as acceptable in their institutional and disciplinary context.

Moving beyond the mystery and magic of data analysis

All research projects require a research design, phases of data collection or data production, and careful processes of analysis that lead to the dissemination of key findings. The activities of analysis have been defined as a process of attention, reflective systematic inquiry, and exploration.

Given its central importance, there could be an assumption that the nuts and bolts of analytical procedures are clear to researchers, and that they are well aware of the steps required to move beyond the mass of data accumulated in a study to the distillation and refinement of key points that attend to research aims and central questions. However, data analysis has been positioned as ‘the most complex and mysterious of all of the phases’ of research and ‘one that receives the least thoughtful discussion in the literature’ (Thorne, 2000, p 69). This impression of mystery and mystical journeys is sustained in the reporting of research studies that only offer a glimpse of the concrete steps of the analytical process.

This mysterious phenomenon, and the lack of insight into the processes by which conceptual leaps that generate abstract theoretical ideas from empirical data, have also been noted by other scholars who call for ‘greater openness and legitimacy for reflexive accounts’ of the ‘how’ of data analysis (Klag and Langley, 2013, p 149).