SOCS: Socially Intelligent Computing to Support Citizen Science

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会能力的显性知识的社会计算系统。该项目将通过调查公众参与科学研究如何能够推进科学目标，同时为志愿者参与者的科学教育做出贡献，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，从而产生社会效益。

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.