Collaborative Research: SEI: Spatio-temporal Data Analysis Techniques for Behavioural Ecology

合作研究：SEI：行为生态学时空数据分析技术

• 批准号: 0431141
• 负责人: Shashi Shekhar
• 金额: $ 57.64万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0431141&HistoricalAwards=false
• 关键词: Collaborative; Research; SEI; Spatio; temporal

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.

1960年，珍·古道尔在坦桑尼亚的贡贝国家公园开始了第一次对人类近亲黑猩猩（Pan troglodytes）的长期实地研究，通过在它们的自然栖息地进行广泛的观察来描述它们的行为。这项研究至今仍在继续，为了解黑猩猩行为和人类进化做出了许多贡献，也激励了世界各地的人们学习科学和致力于野生动物保护。对来自贡贝和其他实地研究（如Kanyawara黑猩猩项目）的完整观测数据集的分析，有可能为许多尚未回答的行为生态学问题提供新的见解，例如群体内社会关系对领土行为的影响。然而，这种观测范式是极其劳动密集型的，迄今为止只分析了贡贝数据集的一小部分。该项目的目标是开始开发数据分析工具和技术，以减少分析观测数据集所需的时间和精力。预期的结果包括一个墨盒挖掘概念模式，一个计算效率高的执行环境，概念模式挖掘，空间半监督学习算法，以提高分类性能，在创建地图。预期的结果将不仅有利于行为生态学家，但也有助于在许多其他时空应用领域的研究，包括基于位置的服务，交通和流行病学。传播计划包括根据贡贝数据开发教学工具，以激励年轻学生学习科学和信息技术，以及举办讲习班，加强计算机科学家和行为生态学家之间的合作。