CyberTraining: DSE: Self-Service Training Modules for Data-Intensive Neuroscience Learning and Research

该项目将开发以网络基础设施为基础的培训模块，以改进用于数据密集型神经科学界学习和研究的现有培训方法。该项目的成果将加强对我们对正常和异常大脑的理解的研究，为NSF推动科学和健康进步的使命做出贡献。这些项目活动将解决由于神经科学研究和教育活动日益成为数据密集型活动而出现的现有培训方法中的重大差距。人们越来越需要整合和分析在多个层面上产生的海量数据，以探索正常和异常大脑的功能。因此，该领域的研究和培训现在需要获取分布式资源，包括多个软件包、具有大量核心的高性能计算、具有数据共享/协作能力的虚拟桌面、神经数据档案，还需要多学科的专业知识(例如，工程学、生物学、心理学)。计算神经科学研究人员、本科生和研究生以及教师(本项目中的三个目标社区)在以可扩展和广泛的方式获取此类资源和专业知识方面面临挑战。此外，它们缺乏使用先进的网络基础设施(CI)技术和分布式资源的必要培训，以提高其科学生产力和进行大规模的数据驱动调查。项目培训模块的变革性在于为这些模块计划的“自助性”，使神经科学用户能够以“按需”和“个性化”的方式使用这些模块。培训模块的开发将基于对培训需求的调查，将侧重于让学生/教师/多学科研究人员使用、应用和创建可在当地(即，在传播与信息机构内部)部署的动手实验室练习和工具，并辅之以可公开获取的国家资源，如国家科学基金会资助的神经科学门户(NSG)。这些培训模块将通过与管理科学工作流程、传播与信息中间件和应用程序编程接口有关的动手实验室练习，极大地加强现有的传统神经科学课程，这些课程涵盖本科、研究生和教师培训层面的基本概念，以整合地理上分散的资源。拟议的活动将利用现有的云计算和神经科学方面的积极培训计划，并将使用NSF支持的高级CI资源，这些资源可在密苏里大学和NSG当地获得。项目成果将被整合到正在进行的课程(其50多名神经科学教员横跨10个系和5所学院)，纳入正在进行的NSF和NIH暑期培训计划，该计划招募不同的参与者，包括服务不足和代表性不足的学生，并纳入正在进行的神经机器人学K-12推广计划。该项目招募的暑期实习生包括50多名学生、神经科学教师和网络基础设施工程师，他们对用于不同研究和教育工作的先进网络基础设施能力感兴趣。此外，80多名学生将受益于密苏里大学现有神经科学和网络基础设施课程的正式课堂课程中的培训模块，150多名学生将受益于包括网络研讨会和会议教程在内的外联活动。

This project will develop cyberinfrastructure-based training modules that advance the existing training methods used for learning and research in data-intensive neuroscience communities. The project outcomes will enhance research into our understanding of both normal and abnormal brains, contributing to NSF's mission of advancing progress in both science and health. The project activities will address important gaps in existing training methods that arise because neuroscience research and education activities are increasingly becoming data-intensive. There is a growing need to integrate and analyze voluminous data being generated at multiple levels to explore the functioning of normal and abnormal brains. Consequently, research and training in the area now necessitates access to distributed resources, including multiple software packages, high-performance computing with large numbers of cores, virtual desktops with data sharing/collaboration capabilities, neuro-data archives, and also requires multi-disciplinary expertise (e.g., engineering, biology, psychology). Computational neuroscience researchers, undergraduate and graduate students and teachers (three targeted communities in this project) face challenges in accessing such resources and expertise in a scalable and extensive manner. Further, they lack the necessary training in the use of advanced cyberinfrastructure (CI) technologies and distributed resources to improve their scientific productivity and to pursue large-scale data-enabled investigations. The transformative nature of project's training modules is in the "self-service" nature planned for the modules that make them accessible to neuroscience users in an "on-demand" and "personalized" manner. The training modules development will be based on survey of training needs, and will be focused on having students/teachers/multi-disciplinary researchers use, apply and create hands-on laboratory exercises and tools that can be deployed locally (i.e., within institutional CI) and be supplemented with publicly accessible national resources such as the NSF-funded Neuroscience Gateway (NSG). The training modules will considerably enhance existing traditional neuroscience courses covering foundational concepts at undergraduate, graduate and teacher-training levels with hands-on laboratory exercises related to managing scientific workflows, CI middleware and application programming interfaces (APIs) to integrate geographically distributed resources. The proposed activities will leverage existing active training programs in cloud computing and in neuroscience, and will use NSF-supported advanced CI resources that are available locally at University of Missouri and at NSG. Project outcomes will be integrated into on-going courses (with its 50+ neuroscience faculty spanning 10 departments, and 5 colleges), into on-going NSF and NIH summer training programs, which recruit diverse participants including under-served and under-represented students, and into an on-going K-12 outreach program in neuro-robotics. The summer trainees that are being recruited in this project include over 50 students, neuroscience faculty and cyberinfrastructure engineers interested in advanced cyberinfrastructure capabilities for diverse research and education efforts. In addition, over 80 students will benefit from the training modules within formal classroom courses in existing neuroscience and cyberinfrastructure courses at the University of Missouri, and over 150 students will benefit from outreach activities that include webinars and tutorials at conferences.