Graduate Student Profiles
Craig McCabe (cam509 [at] psu.edu) graduated in the summer of 2009 with his Master's Degree in Geography, having worked under Dr. Alan M. MacEachren. McCabe's thesis looked at the effects of data complexity and map abstraction on the perception of spatio-temporal patterns in animated maps. Using a 10-year dataset of weekly measles infections in Niger, Craig administered an experiment that employed temporal aggregation and moving-window averaging approaches in combination with geographic and schematic map representations to measure participants' abilities to complete a series of map-reading tasks. During his 2 years as a research assistant at Penn State, Craig collaborated closely with the Center for Infectious Disease Dynamics to create novel methods of exploring patterns and possible environmental drivers of measles epidemics in sub-Saharan Africa.
Craig's Thesis Work
Effects of Data Complexity and Map Abstraction on the Perception of Patterns in Infectious Disease Animations
Geographic map animations have become an increasingly popular method for exploring spatio-temporal datasets. While some have questioned the effectiveness of animations compared to the static alternatives, little research has been done on our ability to retain and recall data presented in animated maps. This study uses a dataset of weekly measles infections in Niger from 1995-2004 in a controlled experiment to test the ability of participants to complete a series of map-reading tasks using choropleth and schematic map representations. Infectious disease data is often imperfectly sampled and inherently noisy. As a result, an important question for map animation designers is whether to represent the raw data directly or to transform the data to dampen the impact of noise. To address this question, the experiment compares animations using the raw weekly data to transformed data sets using temporal averaging and aggregation. These approaches were used to determine what effects data complexity and spatial abstraction have on our ability to perceive spatio-temporal patterns in map animations. Experiment participants (N = 96) were recruited from undergraduate geography classes at Penn State University, then divided into groups according to three data smoothing approaches: raw (weekly) data, 5-week moving-window average, and 2-week aggregation. Participants viewed a series of animations of yearly measles epidemics using three different map representations, then provided quantitative and qualitative assessments of the spatial and temporal characteristics of the infection patterns. The results showed that overall, map representation had a larger impact on task performance than data complexity, due primarily to the perceptual salience of large, but low-population districts in Niger. It was also found that temporal aggregation, an approach used by infectious disease researchers, did not result in any significant interpretation errors overall, despite expectations to the contrary. In some tasks, such as determining when the peak of a yearly epidemic occurred, aggregation proved to be most effective, enabling participants to identify the correct peak week 50% more often, compared to those who used raw data. The results also support the idea that animated maps are best used for simple map-reading tasks or gaining a broad overview of a dataset, and less effective for making quantitative comparisons.
More about Craig's Research
As a research assistant, I spent my first year as a graduate student collaborating with the Center for Infectious Disease Dynamics (CIDD), working on an 11-year dataset of measles incidence in Niger. In the process of exploring spatio-temporal patterns in this highly complex dataset, I began to use animations. One of the first animation efforts looked at the apparent relationship between seasonal vegetative change and the onset of measles epidemics. CIDD researchers had hypothesized that subsistence agriculture was driving seasonal migration in and out of cities, resulting in increased population density in the cities and a corresponding increase in measles transmissions during the dry season. The anti-phase relationship between vegetative "greenness" and measles incidence can be seen in the simple Flash animation linked below. A Gates Foundation grant awarded to CIDD 2008 involved additional resources to the effort, with a focus on transportation pathways and population connectivity - to better understand and improve vaccine supply chain. An animation of a composite year in Niger (11 years of data from 1995-2005 combined, linked below) was used to look for consistencies in outbreak patterns for all years. My interest in map animations and my thesis research topic came about as a direct result of my still ongoing, successful collaboration with CIDD.
In my two years in the Master's program, I have also had the opportunity to contribute to a number other research projects. Drawing from my experience working as a geologist at the USGS prior to returning to graduate school, one of my first papers for Dr. Cindy Brewer's cartography seminar outlined vector generalization approaches for creating multi-scale geologic maps, earning an E. Willard Miller award in Geography. In my 2nd year RA, I also assisted with data and map design on the CalFloraViz web-map (with Tom Auer and Scott Pezanowski) which provides an intuitive means of exploring a large database of plant observations in California, and database, map and poster design for the DC Crime Viz web-map, which won 3rd place at the 2009 DHS Summit student poster competition in Washington D.C. (with Kevin Ross and Robert Roth). Links for these are available below. In addition, I am currently assisting researchers at the GeoVISTA Center with an investigation into the use of the ANSI point symbology standard for emergency management among Department of Homeland Security agencies.