In 1960, Jane Goodall began the first long-term field study of the closest living relatives of humans, chimpanzees (Pan troglodytes), in Gombe National Park, Tanzania to describe their behavior by making extensive observations in their natural habitat. This study, which continues today, has made many contributions to understand chimpanzee behavior and human evolution, and has also inspired people around the world to study science and work toward wildlife conservation. Analysis of the complete observational dataset from Gombe and other field studies, such as the Kanyawara chimpanzee project, has the potential of providing new insights into many unanswered behavioral ecology questions, e.g. the influence of social relationships within the group on territorial behavior.
However, this observational paradigm is extremely labor-intensive and only a small part of the Gombe dataset has been analyzed so far. The goal of this project is to begin developing data analysis tools and techniques to reduce the time and effort required to analyze observation datasets. Expected results include a cartridge for mining concept patterns, a computationally efficient execution environment for concept pattern mining, and spatial semi-supervised learning algorithms to improve classification performance in creating maps. Expected results will not only benefit behavioral ecologists, but also contribute to research in many other spatio-temporal application domains, including location based services, transportation and epidemiology. Dissemination plans include development of instructional tools based on the Gombe data to motivate younger students to learn science and information technology as well as a workshop to increase collaboration between Computer Scientists and Behavioral Ecologists.
