Relational and Metaphorical Approaches to Information Visualization

Emily Hildebrand

CST 591

Review Paper 3

Feb. 14, 2012

Relational and Metaphorical Approaches to Information Visualization:

Effects of Age and Graphical Facility

M.D. Lee & L. Mamykina

Published in: Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting (2005)

Paper citations: 0

The purpose of this paper was to explore and compare the utility of two visualizations for monitoring individual diabetic data. Currently, there are many techniques for manual or automated monitoring of activities and blood sugar levels. However, in the past, designs have not considered user’s differences in ability to interpret displays. For example, many individuals with diabetics are older adults and have difficulty interpreting graphs. Thus, this study compared two types of visualization, relational and metaphorical, to see which one was more effective for managing diabetes in various age groups.

Relational visualizations rely on people’s ability to learn relationships between abstract visual properties of objects (e.g. size, color) to encode information. These visualizations are commonly used to depict data in graphs and bar charts and while they are the visuals that we see most commonly in everyday life, they may not be best suited for an older demographic. This study used the concept of stack timelines which is common in clinical visualizations (Figure 1).

Figure 1. Relational visualization (1 full day).

Metaphorical visualizations are most commonly employed in interface design practices. These visualizations rely on analogies with real world phenomena to communicate information. For this study, the authors chose to use a clock as the metaphor for visualizing data (Figure 2).

Figure 2. Metaphorical visualization (1 full day).

To evaluate the effectiveness of each visualization, the authors recruited 35 participants with diabetes from two age groups: younger (age 25-40) and older (age 60-75). Within the age groups, the authors tried to get people who differed in their ability to interpret graphs. A math test was given to all participants to determine statistical competence and based on those scores, participants were places into a low GF or a high GF group. GF stands for graphical facility and is defined as the general ability to interpret graphs. The participants were then tested on the visualizations. They were presented static pictures of the visualizations and were asked to answer a number of questions including: locating information from a specific reading, forming a hypothesis regarding relationships between data, and identifying overall trends in the data. Questions were measured for accuracy and time for response. The participants were given a scenario of a person with diabetes and their records for one week. When answering questions, participants could look at records for each day separately (Figure 1 and 2), or could view the consolidated visualization for the entire week (Figure 3 and 4).

Figure 3. Relational visualization (Consolidated across 1 week)

Figure 4. Metaphorical visualization (Consolidated across 1 week).

To calculate results, a ANOVA was used where Display Type was the Within Subjects factor and Sex, GF, Age, and Display Type were all between subjects factors. There were main significant effects reported in the article. The first was between display type and GF. Participants with a high GF were faster on the relational displays and participants with a low GF were faster on the metaphorical displays. Overall, the older participants were slower to answer questions than younger participants. The second big effect was that female participants were more accurate with metaphorical displays whereas the male participants were indifferent, equally accurate on both relational and metaphorical. Lastly, preference ratings were recorded and it was found that while older adults rated the two visualizations as equally preferred, the younger adults had a stronger preference for the relational displays.

These findings indicate that there are in fact individual differences that need to be taken into account when designing visualizations. The authors believe metaphorical visualizations are important because they possess “the capability to display information in aesthetically pleasing ways”. However, the authors recognize that more thorough research needs to be done to validate the best visualizations for different types of users and in various contexts.

I chose this paper because I was interested in learning more about human factors considerations that have been explored in the visualization field. I found this particular paper interesting because it introduced and defined two different types of visualizations that I had not yet encountered. Further this paper serves as a good reminder of how varied the user population can be for a single application and that to find the most optimal design, many individual characteristics have to be considered.