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.

该项目由美国国家科学基金会资助，由锡拉丘兹大学的凯文·克劳斯顿（Kevin Crowston）领导，将研究公民科学背景下社会计算支持系统的能力和潜力，公民科学被定义为“回答现实世界问题的志愿者和科学家之间的伙伴关系”。 该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公民科学项目的计算支持。 该项目将重点关注以下三个目标：（1）深入了解社会计算在哪些条件下可以促进科学和教育； （2）生成新的社会计算系统研究模型，支持大规模公众参与科学研究； (3) 开发和测试包含有关人类认知和社交能力的显性知识的社会计算系统。该项目将通过研究如何让公众参与科学研究来推进科学目标，同时为志愿者的科学教育做出贡献，从而产生社会效益参与者，确定公民科学可以证明有利于大规模数据收集和分析的条件，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。