Collaborative Research: ImageQuest: Citizens Advancing Biology with Calibrated Imaging and Validated Analysis

合作研究：ImageQuest：公民通过校准成像和验证分析推进生物学发展

• 批准号: 1053573
• 负责人: Stephen Kobourov
• 金额: $ 28.36万
• 依托单位: University of Arizona
• 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: 2010-10-01 至 2014-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1053573&HistoricalAwards=false
• 关键词: Collaborative; Research; ImageQuest; Citizens; Advancing; Collaborative; Research; ImageQuest; Citizens; Advancing

Washington University, the University of Arizona, University of California San Diego, and the University of Vermont are awarded collaborative grants to develop tools that support deeper integration of citizen scientists with a broader range of biological imaging projects. Our specific aims are to develop tools (1) to make it easier for volunteers with smart phones to capture calibrated imagery supporting quantitative data measurements, (2) to facilitate volunteer contributions to image analysis tasks with better interfaces and formal methods to validate and create consensus estimates from many responses, and (3) to foster long-term motivation and engagement within virtual communities through online environments that combine aesthetics, social networking and visualization tools. These tools will have an initial focus on problem domains including monitoring of urban re-forestation efforts and analysis of 3D biological and neurological imaging data at many different scales. It will produce a set of smart phone and web apps that will be available to the broader biological research community that require calibrated image capture and analysis, and will create an experimental web portal to engage virtual communities of volunteers and scientists collaborating to work on imaging problems.The ImageQuest project will make it simpler for volunteers and scientists to engage in a much broader set of biological imaging research. Providing tools which enhance a volunteers ability to capture and analyze images relieves a technical burden on biologists trying to develop citizen science approaches. Making these tools smarter and more interactive encourages volunteers to contribute meaningfully to novel research questions, and building a virtual community around the volunteers and the scientists helps to recruit, motivate and retain long term participation of the public in scientific research.

华盛顿大学，亚利桑那大学，加利福尼亚大学圣地亚哥大学和佛蒙特大学获得合作赠款，以开发工具，以支持更深入的公民科学家与更广泛的生物成像项目的更深入整合。 我们的具体目的是开发工具（1），以使拥有智能手机的志愿者更容易捕获支持定量数据测量的校准图像，（2），促进志愿者对图像分析任务的贡献，并具有更好的接口和正式方法，以验证和（通过在线范围内促进社交范围）促进和（3）促进社会范围，以及（3），以及（3），（3），以及（3），（3）促进了社会的范围，并（3）促进了社会的范围，并促进了社会的范围，并（3）促进美德的范围，并促进美德的范围。和可视化工具。 这些工具将最初关注问题领域，包括监视城市重新造林工作以及在许多不同尺度上对3D生物学和神经系统成像数据的分析。 它将生产一套智能手机和网络应用程序，这些应用程序将为更广泛的生物学研究社区提供，需要校准的图像捕获和分析，并将创建一个实验性的Web门户网站，以吸引志愿者和科学家的虚拟社区，以合作进行成像。提供工具，以增强志愿者捕获和分析图像的能力，从而减轻了试图开发公民科学方法的生物学家的技术负担。 使这些工具更加聪明，更互动，鼓励志愿者为新的研究问题做出有意义的贡献，并围绕志愿者和科学家建立虚拟社区，有助于招募，激励和保留公众在科学研究中的长期参与。