AN OPEN RESOURCE FOR COLLABORATIVE BIOMEDICAL BIG DATA TRAINING

协作生物医学大数据培训的开放资源

• 批准号: 8935849
• 负责人: Ilkay Altintas de Callafon
• 金额: $ 21.57万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-29 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8935849
• 关键词: Address; Award; Big Data; Biomedical Research; Biometry; Boxing; Camping; Case Study; Clinical; Communities; Complex; Computer Assisted; Data; Data Set; Development; Drug Design; Education; Educational Curriculum; Ensure; Environment; Faculty; Foxes; Future; Genomics; Goals; Growth; Health; Human; Image; Investigation; Knowledge; Learning; Learning Module; Metagenomics; Mission; Modeling; Ontology; Persons; Research; Research Personnel; Resources; Science; Scientist; Students; Technology; Testing; Training; Training Programs; Training and Education; United States National Institutes of Health; Vision; Work; base; biomedical scientist; cloud based; data management; drug discovery; insight; instructor; interoperability; lectures; next generation; repository; skills; success; teacher; tool; virtual

DESCRIPTION: Of all the resources required to make gaining insight from big data a success, perhaps the most important is the human one. A major challenge to the big data community generally and especially, the biomedical big data community is training and education of the current and next generation of biomedical scientists. We must work collectively to address this critical challenge. What we seek to do through this proposed project is maximize the impact of biomedical big data training through a large-scale collaborative approach, and to create a training and education framework for other educators (a.k.a., teachers, instructors) and/or learners (a.k.a., students, trainees, researchers) that enables them to construct and deliver customized modules or courses that deliver the highest value to their particular application. Our vision is to cultivate a high-quality, well-informed, freely accessible knowledge and data community effort around training and education in biomedical big data research, through the Biomedical Big Data Training Collaborative (BBDTC). The end-to-end BBDTC open online training framework is a repository allowing faculty, researchers and students access to a state-of-the-art training model over the years to come. To develop such an environment, we employ current best practices and build upon our existing efforts. Initially we focus on building the BBDTC along with example courses, lecture content and hands-on application use cases for biomedical big data training. We will also communicate best practices for developing course content and delivering it to a wide-range of trainees along with associated adaptive learning approaches and assessments. In addition, we will deliver customizable virtual machines (VMs) including the course materials, hands-on tools and example data and additional assessment and make sure that these VMs are portable to a variety of environments. Specific aims in the project include development of: (1) Biomedical Big Data Curriculum; (2) Biomedical Big Data MOOC Framework; (3) Biomedical Big Data Tool Box; and (4) Repository Interfaces to Engage Community Stakeholders. The significance of our approach is that the BBDTC will enable the development of many more courses and training modules (whether they are full-scale MOOCs or much smaller, more targeted units). Although we focus on the present "mission critical" challenges defined by the NIH and biomedical community, we build the BBDTC framework in a way that will allow it to evolve over the years, not just by one person but by a community of biomedical big data researchers as a collective force to handle training challenges of the future.

描述：在从大数据中获得洞察力所需的所有资源成功，也许最重要的是人类。一般，尤其是生物医学大数据社区的主要挑战是对当前和下一代生物医学科学家的培训和教育。我们必须集体努力以应对这一关键挑战。我们试图通过这个提议的项目要做的是通过大规模的协作方法最大化生物医学大数据培训的影响，并为其他教育者（又称教师，教师，教师）和/或学习者（又称学生，学生，受训者，研究人员）创建培训和教育框架，以使他们能够构建和交付自定义的模型或交付自定义的模型或交付自定义的模型。我们的愿景是通过生物医学大数据培训协作（BBDTC）来培养围绕生物医学大数据研究中的培训和教育的高质量，信息良好，可自由获取的知识和数据社区努力。端到端的BBDTC开放在线培训框架是一个存储库，可在未来几年中允许教师，研究人员和学生访问最先进的培训模型。为了发展这样的环境，我们采用了当前的最佳实践，并基于我们现有的努力。最初，我们专注于构建BBDTC以及用于生物医学大数据培训的示例课程，讲座内容和动手应用程序用例。我们还将传达最佳实践，以开发课程内容并将其交付给广泛的学员，以及相关的自适应学习方法和评估。此外，我们还将提供可自定义的虚拟机（VM），包括课程材料，动手工具和示例数据以及其他评估，并确保这些VM可移植到各种环境中。该项目的具体目的包括：（1）生物医学大数据课程； （2）生物医学大数据MOOC框架； （3）生物医学大数据工具盒； （4）与社区利益相关者相关的存储库界面。我们方法的意义在于，BBDTC将能够开发更多的课程和培训模块（无论是全尺度的MOOC还是更小，更具针对性的单位）。尽管我们专注于NIH和生物医学界定义的当前“任务批判性”挑战，但我们以一种将使它多年来发展的方式建立了BBDTC框架，而不仅是一个人，而且是由一个生物医学大数据研究人员社区作为集体的集体力量，可以应对未来的培训挑战。