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

数据驱动的方法在推进生物工程研究方面具有重要作用。生物工程网络培训计划为未来的研究人员和从业者配备了数据驱动的方法，这些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，通过培训本科生生物工程学生以及生成和发布培训材料和实践项目数据，促进包容性，并造福社会。该计划确保了广大受众的可及性，并促进了STEM领域的多样性。它通过强调团队建设、公平(可发现、可访问、可互操作和可重复使用)的数据原则和真实世界的项目来推动数据驱动的生物工程教育。该计划提供了涵盖数据科学概念、工作流程、可视化、公平数据原则和分析的综合课程，重点是将这些原则应用于生物工程领域。该计划包括一个新兵训练营，一个为期10周的动手培训计划，以及一个带有海报竞赛的研究研讨会。该项目强调团队建设、与代表性不足的群体的接触以及与行业合作伙伴的合作，以增强学生的能力，使他们能够从事真实世界的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，补充指导部分的动手指导项目部分，以及基于团队的项目部分。以团队为基础的项目部分将学生团体与来自行业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NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.