Promoting Institutional Communities for Open Data Science

 描述(申请人提供)：在我们这个快速发展的信息时代，处理在生物医学研究中获得的大量数据的方法已经成为应对关键研究问题的强大工具，在从基因组学到健康信息学到环境研究的不同领域产生了重大影响。NIH的大数据到知识(BD2K)培训联盟预计将使当前和未来一代研究人员全面了解数据科学生态系统：探索、准备、分析、可视化和解释大数据的能力。为此，我们提出了一个新的培训协调中心(TCC)，以协调BD2K培训联盟内发生的各种活动，使其成为协同培训工作。技术合作中心将创建一个名为“大数据U”的包容性和协作性虚拟环境，为来自不同教育背景和科学领域的学员提供服务。大数据大学将使个性化的教育资源更容易访问，并通过科学轮换促进新颖的研究合作。我们将收获网络，以自动识别、建模在线资源，并将其纳入教育资源发现索引(EURUDITE)和大数据U知识地图。这一独特的系统将减轻在数百个教育资源中筛选和在多个研究和培训计划网站上搜索的负担，使用户能够轻松确定哪些资源具有教学意义，并与感兴趣的科学领域、教育水平和学习目标相对应。超过了 从长远来看，我们的努力将培养一个多样化的数据科学家网络，能够传播他们的 世世代代的知识和经验。我们的PI和团队对生物医学数据科学方面的培训有着明确的承诺。南加州大学非常适合主办这项NIH BD2K项目，该校在数据科学培训方面有着深厚的历史，最近还创建了两个与大数据生物医学相关的新硕士项目。TCC是我们在数据科学方面杰出记录的合理延伸，我们将利用我们的全面经验和基础设施来开发TCC。

 DESCRIPTION (provided by applicant): In our rapidly evolving information era, methods for handling large quantities of data obtained in biomedical research have emerged as powerful tools for confronting critical research questions, with significant impacts in diverse domains ranging from genomics to health informatics to environmental research. The NIH's Big Data to Knowledge (BD2K) Training Consortium is expected to empower current and future generations of researchers with a comprehensive understanding of the data science ecosystem: the ability to explore, prepare, analyze, visualize, and interpret Big Data. To these ends, we propose a novel Training Coordinating Center (TCC) to coordinate the diverse activities occurring within the BD2K Training Consortium into a synergistic training effort. The TCC will create an inclusive and collaborative virtual environment - entitled "Big Data U" - serving trainees from a wide spectrum of educational backgrounds and scientific domains. Big Data U will make personalized educational resources easy accessible and facilitate novel research collaborations through scientific rotations. We will harvest the web to automatically identify, model, and incorporate online resources into an Educational Resource Discovery Index (ERuDIte) and a Big Data U Knowledge Map. This unique system will alleviate the burden of sifting through hundreds of educational resources and searching across multiple research and training program websites, allowing users to easily determine which resources are didactically significant and correspond to the appropriate scientific domain of interest, level of education, and learning objective. Over the long term, our efforts will cultivate a diverse network of data scientists that can propagate their knowledge and experience for generations to come. Our PI and team have a demonstrated commitment to training in biomedical data science. The University of Southern California is ideally suited to host this NIH BD2K effort, having a strong history of data science training and recently founded two new masters programs of relevance to Big Data biomedicine. The TCC is the logical extension of our outstanding track record in data science, and we will leverage our comprehensive experience and infrastructure in developing the TCC.