Visualizing Qualitative Information.

Introduction Humans instinctively rely on qualitative information. When there were no clocks, they coordinated activities by phases of the sun and moon; later, by sundials and hourglasses. It was not until the invention of clocks, watches, and calendars that people synchronized their lives around specific numbers. Today, numbers are used in abundance to help describe opinions, tendencies, feelings, needs and other concepts because they are seen as more manageable and efficient than text-based qualitative information. For the sake of efficiency, a coffee drinker may forego the exact amount of desired sweetness by using a packaged gram of sugar rather than measuring until the taste is "just right." An information scientist may measure the performance of a search system by calculating its ratio of recall (finding "wanted" items) to precision (success in excluding unwanted items) rather than talking to end-users who cannot always articulate what they need but know it when they see it. Yet, if one needed to capture the exact moment when two people want to meet, precisely the amount of sugar that makes a cup of coffee "sweet enough" or the "right" information for a computer user, one must rely on qualitative approaches. Normally, qualitative research is presented using narrative and the occasional table. Both of these methods are appropriate for "telling" the story about the results. Imagine, however, being able to "show" the story by way of displays that assist with analysis and sharing of qualitative data results. Amid a discussion of the need for more powerful qualitative analysis and visualization tools, this article presents a device that takes us toward better representations of qualitative results. Why We Need Graphical Displays Qualitative researchers have the formidable task of capturing, sorting, analyzing, interpreting, and sharing qualitative data. With the help of qualitative software, they have succeeded in capturing, recording, and sorting information. What would the qualitative world look like if they were able to visually capture qualitative phenomena? Two potential outcomes of this ability are the increase in both analytical power and credibility of qualitative results. Analytical Power Thorne (2000) describes qualitative analysis as "confusing" because of the mystery often surrounding the way study results evolve from the data. This demonstrates the need for tools that help users visually analyze findings, share results and connect data directly to findings. Support for the graphical display of information using primarily quantitative data is well documented (Cleveland & McGill, 1984; Lockwood, 1969; Schmid & Schmid, 1979; Tufte, 1983; Wallgren, Wallgren, Persson, Jorner, & Haaland, 1996). However, little is known about the graphical display of qualitative data. Software currently available for qualitative researchers ranges from simple databases for searching, sorting, and retrieving to visually editable displays that take full advantage of data imported from any number of sources (Lewins & Silver, 2009; Weitzman & Miles, 1995). Though the software saves time, it does not fundamentally change the way qualitative data are analyzed and represented (Coffey, Holbrook, & Atkinson, 1996; Dohan & Sanchez-Jankowski, 1998). No qualitative analysis tool has the analytic power, visual effectiveness, and universality of quantitative tools like pie charts, bar charts, and scatter-plots. A picture has the means to communicate ideas, relationships, situational dynamics and other concepts in a qualitative dataset. It is up to qualitative researchers to provide the pictures. Credibility A graphical display of qualitative information may address transferability and confirmability, two of the four criteria set out by Lincoln and Guba (1985) as elements of trustworthiness in qualitative research. …