The world we live in is dynamic on all scales. On a small scale, think of walking across a room or driving to the grocery store; on a large scale, imagine a hurricane crossing a state. Research that addresses how humans understand relationships between space and time is, therefore, central not only to geography, but also to cognitive and information sciences. The objectives of this project are two-fold: to develop a research framework for examining how movement patterns at the geographic scale (MPGS) are understood, and to evaluate how formalisms used in geographic information science are able to capture how people understand MPGS. Linking cognitive and formal characterizations enables models that align with how people think about large scale spatial processes, thereby enhancing communication at the interface between humans and computers.
Dr. Alexander Klippel at the Pennsylvania State University will conduct a set of experiments that are based on a grouping paradigm that is used to elicit conceptual knowledge (i.e., categorization). Participants view animations of large-scale spatial phenomena ending at different spatio-temporal stages. For example, participants will look at 63 different animations of a hurricane approaching shore, making landfall, and finally moving far inland. Participants will then classify these animations based on their similarities. The question these studies are attempting to answer is whether formal, topologically equivalent characterizations across different domains (e.g., whether the moving entity is a hurricane or a glacier) are also equivalent cognitively. In other words, how does the semantics of dynamic features influence the cognitive conceptualizations thereof? Does semantics change the cognitive salience of individual topological relations? Additionally, the project will address the geographically critical question of scale effects and a contribution will be made to the formal underpinning of geographic event language by relating the conceptualizations of movement patterns to linguistic externalizations. To accomplish these goals, the PI has developed software to both collect and analyze behavioral data efficiently. The software to analyze the data will be developed within existing geovisual analytics software developed at the GeoVISTA Center in the Geography Department at the Pennsylvania State University.
This project will contribute to the understanding of how humans conceptualize movement patterns at the geographic scale, such as hurricanes moving across a peninsula, from the perspective of how these movement patterns are characterized formally. Connecting formal and cognitive characterizations of spatio-temporal information is essential to develop efficient human-computer interfaces and models of spatial cognition. This project will develop software solutions for the design of experiments and the efficient analysis of the collected data using visual analytics approaches. As cognitive conceptualizations are core to research on ontologies and categorization, and also to fields such as anthropology, we expect both the developed research framework and the software solutions to be beneficial to a large research community.
