Lengler, R. & Eppler, M. (2007). Towards a periodic table of visualization methods for management. IASTED Proceesing of the Conference on Graphics and Visualization in Engineering. Lecture conducted from Clearwater, FL. In this article, Lengler and Eppler (2007) discuss the current state of data visualization as an area of academic inquiry; define their focus in visualization type and usage; and develop an infomap designed to group like methods of visualization for researcher and educator ease. A visualization, for the purposes of this article, is defined by Lengler and Eppler as
“a systematic, rule-based, external, permanent and graphic representation that depicts information in a way that is conducive to acquiring insights, developing an elaborate understanding, or communicating experiences” (pp. 1).
Data visualization as a fractured field
Lengler and Eppler (2007) open with a reflection upon the current state of data visualization literature. Described as an “emergent” (pp. 1) field, work on data visualization is fractured across multiple, disparate fields—from computer programming to education. The danger with this, the authors note, is the possibility that scholars may pursue theoretical work or breakthrough ideas in parallel with each other, rather than building collaboratively from each other’s works; this, in turn, could impede the development of data visualization research as its own distinct field. This characterization—a highly dichotomous bed of literature—reminds me strongly of Dr. Jordan’s (2014) thoughts on her work in researching educational “uncertainty.” Much of the literature foundational for her thesis comes from disciplines focusing upon organization or management; likewise, this discussion of categorizing data visualizations is heavily rooted in management research, perhaps owing to Eppler and Lengler’s management backgrounds.
Overlap between management and education
Lengler and Eppler hone in upon visualization methods that are easily applicable within the field of management; that is, methods that are outcome oriented and favor a strong focus upon problem solving. Because of this problem-solving focus, most if not all of the visualization methods presented are easily translatable to an educational (or more specifically classroom) environment. As the authors interpret it, the “key for better execution is to engage employees” (pp. 2). Through an educational lens, the same could be said of the need for educators to engage their students; Howard (2003) would certainly agree with the importance in considering what Lengler and Eppler term cognitive, social and emotional challenges facing managers; visualization methods, to their end, are tools—“advantages” (pp. 2)—to better understand and incorporate the perspectives of employees, and should either help to simplify a discussion or to foment new ideas and innovations. This, of course, can is also true in reverse: A good visualization will give employees as much insight into their managers as vice versa.
The data visualization of data visualizations
In order to walk the walk, so to speak, the authors create a visualization—specifically, an infomap—to categorize and explore relationships between particular methods of displaying or interacting with data. They chose visualization methods that were problem-solving or outcome oriented, per their focus on managerial research. They also chose visualization methods that are easy to produce (though they may vary in complexity). This infomap is visually based upon the Periodic Table of Elements. The authors note that the Periodic Table, in particular, is an excellent example of a co-opted visual metaphor; while widely recognized and used within several scientific fields, including chemistry, the Periodic Table is also understood outside of a scientific context as a shorthand to group or describe a complex topic. Their “Periodic Table of Visualization Methods” is given as one of many examples of nonscientific fields using both the structure and shorthand connotation of the Periodic Table to describe something completely beyond chemical elements.
(Lengler & Eppler, 2007)
To help guide their discussion, Lengler and Eppler codify visualization methods on several axes, beginning first with their complexity and application. Complexity is visualized as an ordinal characteristic; that is, the authors line up like methods in columns, from simplest at the top to most complex at the bottom. Application is a bit more complex. Methods are categorized by color into one of six “groups”:
- Data visualizations, or “visualizations of quantitative data in schematic form” (pp. 3);
- Information visualizations, or “the use of interactive visual representations of data to amplify cognition” (pp. 3);
- Concept visualizations, or “methods to elaborate (mostly) qualitative concepts…through the help of rule-guided mapping procedures” (pp. 3-4);
- Metaphor visualizations, or “effective and simple templates to convey complex insights” (pp. 4), such as story lines;
- Strategy visualizations, or the “systematic use of complementary visual representations to improve the analysis, development, formulation, communication and implementation of strategies in organizations” (pp. 4); and
- Compound visualizations, or methods that combine two or more of the following groupings or formats.
However, the authors also note that the categories listed above are not mutually exclusive; visualization methods can and do belong to multiple “groups.” They attempted to streamline this process by focusing on both the complexity of a method—removing compound visualizations from ambiguity—and its interactive intent. In addition to grouping like methods, Lengler and Eppler also attempt to systematically categorize each method in their chart. They focus on interaction, or the strengths of a visualization: Does it provide an excellent summary or overview of data, or does it better drill down into the details? The authors also take into account what they term “cognitive processes” (pp. 4): Is the visualization an aid to simplify a complex concept (convergent thinking), or does it better jumpstart new and innovative ideas (divergent thinking)? To view the full infomap in all its interactive glory, with scroll over examples of all visualization methods listed, please visit: http://www.visual-literacy.org/periodic_table/periodic_table.pdf
Jordan, M. (2014, June). Managing uncertainty during collaborative problem solving in elementary school teams. Lecture conducted from Arizona State University, Phoenix, AZ.
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