Beyond Text

Abstract

Recent methodological debates in sociology have focused on how data and analyses might be made more open and accessible, how the process of theorizing and knowledge production might be made more explicit, and how developing means of visualization can help address these issues. In ethnography, where scholars from various traditions do not necessarily share basic epistemological assumptions about the research enterprise with either their quantitative colleagues or one another, these issues are particularly complex. Nevertheless, ethnographers working within the field of sociology face a set of common pragmatic challenges related to managing, analyzing, and presenting the rich context-dependent data generated during fieldwork. Inspired by both ongoing discussions about how sociological research might be made more transparent, as well as innovations in other data-centered fields, the authors developed an interactive visual approach that provides tools for addressing these shared pragmatic challenges. They label the approach “ethnoarray” analysis. This article introduces this approach and explains how it can help scholars address widely shared logistical and technical complexities, while remaining sensitive to both ethnography’s epistemic diversity and its practitioners shared commitment to depth, context, and interpretation. The authors use data from an ethnographic study of serious illness to construct a model of an ethnoarray and explain how such an array might be linked to data repositories to facilitate new forms of analysis, interpretation, and sharing within scholarly and lay communities. They conclude by discussing some potential implications of the ethnoarray and related approaches for the scope, practice, and forms of ethnography.

Approaches to decision-making among late-stage melanoma patients: a multifactorial investigation

“…We overview the study's methods here. Additional details of the study design and procedures are available elsewhere [34][35][36][37].…”

“…Second, patterns within the heatmap can be identified using computational techniques found in inductive statistical approaches and data science. The ethnoarray methodology has been described in detail elsewhere [34,35].…”

A mixed-methods framework for analyzing text data: Integrating computational techniques with qualitative methods in demography

“…Across disciplines, social scientists are converging around new ethical standards of transparency and replicability, demanding that researchers publicly share their data and analysis files in order to provide an evidentiary basis for claims (Miguel et al 2014). Despite recognizing the unique challenges that qualitative data poses, including the need to preserve the anonymity of subjects and the likelihood that multiple interpretations will emerge from the same data source, qualitative researchers have also been called upon to focus on the twin problems of transparency of data and transparency of making claims (Abramson and Dohan 2015;Elman and Kapiszewski 2014;Freese 2007;King, Keohane, and Verba 1994).…”

Visualization of Multidimensional Data in Nursing Science

“…As will be demonstrated in two exemplar studies, scientific visualization can be used with any type of data including numbers, text, images, or a mixture (Abramson & Dohan, 2015; Knigge & Cope, 2006; Onwuegbuzie & Dickinson, 2008). The analytic objective is to transform and integrate data sets into visual representations, using a well-understood, transparent, and reproducible process, such that it allows the researcher to search visually for patterns or trends in varied configurations of the data.…”

“…Interesting applications of interactive visualizations abound in the literature. For example, sociologists Abramson and Dohan (2015) illustrate the use of an ethnoarray, loosely adapted from the microarray or graphical heatmap approach, for analyzing, representing, and sharing ethnographic data.…”