SOCS: Socially Intelligent Computing to Support Citizen Science

SOCS：支持公民科学的社会智能计算

• 批准号: 0968470
• 负责人: Jun Wang
• 金额: $ 47.89万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968470&HistoricalAwards=false
• 关键词: SOCS; Socially; Intelligent; Computing; Support

The NSF-funded project conducted by Kevin Crowston at Syracuse University will investigate the capabilities and potential of social-computational support systems in the context of citizen science, defined as "partnerships between volunteers and scientists that answer real-world questions". The research will examine nature of the computational systems currently used in a number of citizen science projects and will use these insights to improve computational support for different kinds of citizen science projects. The project will focus on the following three goals: (1) developing a practical understanding of the conditions under which social computation can enhance science and education; (2) generating new research models of social-computational systems that support large-scale public participation in scientific research; and (3) developing and testing social-computational systems that incorporate explicit knowledge about human cognitive and social abilities.The project will produce societal benefits by investigating how involving the public in scientific research can advance scientific goals while contributing to the science education of the volunteer participants, determining the conditions under which citizen science can prove beneficial for large-scale data collection and analysis, and providing guidelines for improving the design and implementation of computational support systems for citizen science projects.

这项由美国国家科学基金会资助的项目由锡拉丘兹大学的凯文·克劳斯顿主持，将在公民科学的背景下调查社会计算支持系统的能力和潜力，公民科学的定义是“志愿者和科学家之间的伙伴关系，他们回答现实世界的问题”。这项研究将检查目前在许多公民科学项目中使用的计算系统的性质，并将利用这些见解来改善对不同类型的公民科学项目的计算支持。该项目将集中于以下三个目标：(1)发展对社会计算可以促进科学和教育的条件的实际理解；(2)产生支持大规模公众参与科学研究的社会计算系统的新研究模型；以及(3)开发和测试包含关于人类认知和社会能力的明确知识的社会计算系统。该项目将产生社会效益，方法是调查让公众参与科学研究如何在促进志愿参与者的科学教育的同时促进科学目标，确定公民科学在什么条件下可以证明有利于大规模数据收集和分析，并为改进公民科学项目计算支持系统的设计和实施提供指导方针。