Collaborative Research: CyberTraining: Pilot: Cybertraining to Develop FAIR Data Competencies for Bioengineering Students

合作研究：网络培训：试点：通过网络培训为生物工程学生培养公平数据能力

• 批准号: 2321122
• 负责人: Reem Khojah
• 金额: $ 15万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321122&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Pilot; Cybertraining

Data-driven methods have a significant role in advancing bioengineering research. The bioengineering cyber training program equips future researchers and practitioners with data-driven methods that can be applied to a wide-range of engineering problems. The program supports data-driven bioengineering education, fosters inclusivity, and benefits society through the training of undergraduate bioengineering students and the generation and release of training material and hands-on project data. The program ensures accessibility to a wide audience and promotes diversity in STEM fields. It advances data-driven bioengineering education by emphasizing team building, FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, and real-world projects.The program provides a comprehensive curriculum covering data science concepts, workflows, visualizations, FAIR data principles, and analytics, with a specific focus on applying these principles in the field of bioengineering. The program includes a boot camp, a 10-week hands-on training program, and a research symposium with a poster competition. The program emphasizes team building, outreach to underrepresented groups, and collaboration with industry partners to empower students and enable them to work on real-world data-driven bioengineering projects. The 10-week training program includes three components: an instructional component that covers the principles of data-driven bioengineering, a hands-on guided project component that complements the instruction part, and a team-based project component. The team-based project component matches student groups with partners from industry and academia to allow students the opportunity to work on real data-driven bioengineering problems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

数据驱动的方法在推进生物工程研究中具有重要作用。生物工程网络培训计划为未来的研究人员和实践者提供数据驱动的方法，可以应用于广泛的工程问题。该计划支持数据驱动的生物工程教育，促进包容性，并通过培训本科生物工程学生以及生成和发布培训材料和实践项目数据来造福社会。该计划确保了广泛受众的可访问性，并促进了STEM领域的多样性。它通过强调团队建设、FAIR（可查找、可访问、可互操作和可重用）数据原则和现实世界的项目来推进数据驱动的生物工程教育。该计划提供了一个全面的课程，涵盖数据科学概念，工作流程，可视化，FAIR数据原则和分析，特别侧重于在生物工程领域应用这些原则。该计划包括一个新兵训练营，一个为期10周的实践培训计划，以及一个带有海报比赛的研究研讨会。该计划强调团队建设，向代表性不足的群体伸出援助之手，并与行业合作伙伴合作，赋予学生权力，使他们能够在现实世界中从事数据驱动的生物工程项目。为期10周的培训计划包括三个部分：涵盖数据驱动生物工程原理的教学部分，补充教学部分的实践指导项目部分，以及基于团队的项目部分。基于团队的项目组件将学生团体与工业界和学术界的合作伙伴相匹配，使学生有机会研究真正的数据驱动的生物工程问题。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。