Workshop on: Discovery in Complex or Massive Datasets: Common Statistical Themes

为支持当代科学而产生的数据量和复杂性继续快速增长。在从基因组学到气候科学的各个领域，统计学家都在积极参与跨学科研究团队。统计学的历史表明，虽然统计方法和理论经常是为了应对诸如这些特定科学领域的挑战而出现的，但从后来应用于远离起源的学科的过程中，统计方法和理论往往实现了它们的全部范围和力量。因此，对“交叉点”--与科学研究的多个领域相关的统计问题、理论和方法--的研究，在当今的信息时代提供了巨大的机会。拟议的讲习班回应了这个机会：它的目的是列举这些交叉点产生的当今在智力上最具说服力的统计挑战，以期刺激未来的研究进展，从而扩展和加强我们的科学发现数据分析工具包。研讨会的会议记录和讨论将提炼成一份10-15页的报告，由国家科学基金会通过其网站和其他常规渠道广泛传播。这份研讨会和报告回应了一些迫切的国家需求：a)通过提高统计理论和方法对从海量和/或复杂数据集中发现数据做出贡献的能力，加强国家研究的“方法论基础设施”；b)通过促进统计交叉研究，推进研究统计学家的博士后和博士后水平的培训，他们将是美国在扩大统计学研究生和本科学位课程方面急需的核心教员；c)促进学科之间的思想交流，因为一个领域开发的分析方法被转移到其他领域。

The amount and complexity of data generated to support contemporary science continues to grow rapidly. In domains from genomics to climate science, statisticians are actively engaged in interdisciplinary research teams. The history of statistics shows that, while frequently arising in response to challenges in specific scientific domains such as these, statistical methods and theory often achieve their full range and power from later application to subjects far remote from those of origin. The study of the ``intersections'' -- statistical problems, theories and methods that are relevant to multiple domains of scientific enquiry -- thus offers great opportunity in today's Age of Information.The proposed workshop responds to this opportunity: it aims to enumerate today's most intellectually compelling statistical challenges arising out of these intersections, in the hope of stimulating future research advances that will extend and enhance our data analytic toolkit for scientific discovery. The proceedings and discussions of the workshop will be distilled into a 10-15 page report, which will be disseminated widely by NSF through its website and other usual channels. This workshop and report respond to a number of compelling national needs: a) enhancing the nation's ``methodologic infrastructure'' for research, by advancing the capability of statistical theories and methods to contribute to discovery from massive and/or complex datasets, b) through promotion of research on statistical intersections, to advance the pre- and post- doctoral level training of research statisticians who will be critically needed core faculty members in expanding graduate and undergraduate degree programs in statistics in the U.S., c) fostering the flow of ideas between disciplines, as analysis methods developed in one domain are transferred in other areas.