La Serena School for Data Science: Applied Tools for Astroinformatics, Biomedical Informatics, and Other Data-driven Sciences

拉塞雷纳数据科学学院：天文信息学、生物医学信息学和其他数据驱动科学的应用工具

• 批准号: 1637359
• 负责人: Charles Mattias Mountain
• 金额: $ 58.24万
• 依托单位: Association of Universities for Research in Astronomy, Inc.
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1637359&HistoricalAwards=false
• 关键词: La; Serena; Data; Science; Applied

The volume and complexity of scientific data continue to grow rapidly. New astronomical surveys will result in datasets much larger than those previously available. This poses new challenges for data-driven discovery. It also enables new opportunities for interdisciplinary research. Astronomy is at the forefront in creating "pi-shaped" data scientists. These people have both science expertise and cross-disciplinary knowledge. Many other fields also see the need for such pi-shaped scientists. The La Serena School for Data Science 2017-2021 will introduce undergraduates and graduates to the tools and techniques they need. They will be ready just in time for the large scientific projects of 2020 and beyond.The existence of enormous (peta-scale) datasets coming from wide-area and time-domain astronomical surveys poses significant concerns for data-driven discovery, access, and analysis, even while enabling new opportunities for interdisciplinary research in applied mathematics, statistics, machine learning, and related topics. Astronomy provides a sandbox where scientists can come together from diverse fields to address common challenges within the "Big Data" paradigm. The one-week La Serena School, each year from 2017 to 2021, will train the next generation of scientists in astronomy, biomedicine, computer science, statistics, and mathematics, from the US, Chile and other countries, in the tools and techniques of massive data. With the experience gained from this school, participants will be prepared to lead the exploration of the extremely large datasets of tomorrow. The pilot schools, held from 2013 to 2015, were very successful, both demonstrating the demand, and building a strong foundation for collaboration between the NSF and Chilean institutions. This award will bring 15-18 U.S. students, roughly half of the class each year, to Chile for a combination of learning about massive data and working side-by-side with their Latin-American and other international colleagues. Support for the schools is shared with a diverse set of Chilean institutions. NSF funding is provided by the Office of International Science and Engineering and the Directorate for Mathematical and Physical Sciences.

科学数据的体积和复杂性继续迅速增长。 新的天文调查将导致数据集比以前可用的数据集大得多。 这为数据驱动的发现带来了新的挑战。 它还为跨学科研究带来了新的机会。 天文学在创建“ PI形”数据科学家方面处于最前沿。 这些人既有科学专业知识，又具有跨学科知识。 许多其他领域还认为需要这种PI形科学家。 La Serena数据科学学校2017-2021将向本科生和毕业生介绍所需的工具和技术。 他们将及时准备2020年及以后的大型科学项目。来自广阔区域和时间域天文调查的巨大（PETA尺度）数据集对数据驱动的发现，访问和访问和访问构成了重大关注。分析，即使在应用数学，统计，机器学习和相关主题方面为跨学科研究带来了新的机会。 天文学提供了一个沙盒，科学家可以从不同的领域聚集在一起，以应对“大数据”范式中的共同挑战。 每年从2017年到2021年，一周的LA Serena学校将培训来自美国，智利和其他国家 /地区的天文学，生物医学，计算机科学，统计和数学的下一代科学家大量数据。 随着这所学校获得的经验，参与者将准备领导明天极大的数据集探索。 从2013年到2015年举行的试点学校非常成功，既表明了需求，又为NSF和智利机构之间的合作奠定了坚实的基础。 该奖项将使每年大约15-18名美国学生的一半占一半，以了解有关大量数据以及与拉丁美洲和其他国际同事并肩工作的结合。 对学校的支持与各种各样的智利机构共享。 NSF资金由国际科学与工程办公室以及数学和物理科学局提供。