Data Management and Analysis Core

项目摘要 Emory ACE数据管理和分析核心的目标是创建一个最佳的科学和 从密集采样的纵向数据中创建社会参与增长图的技术环境 集共同注册跨多个领域，以探索社会偶然性在自闭症和关键的周期， 发展的过渡，项目I-V以及整个计划项目的关键目标。为了实现这一 为了实现这一目标，核心将为数据收集、处理、分析 存储和检索，以服务于整个计划项目，以及作为一个共同的知识库共享 数据之间的个别项目和传输结果NDAR。核心的具体目标是：（1）数据 管理：满足具有独特挑战性的数据处理、管理、存储和传输需求 （2）数据分析：提供一个共同的方法框架， 计算基础设施，以进行最先进的发展概况分析和统计分析， （3）培训和可靠性：提供以下方面的共同培训： 所有新的数据分析技术在项目中使用，并确保这些技术 使用适当的数据管理程序，在各个项目中一致、可靠地部署;以及（4） 质量控制：确保项目产生的所有数据都具有一致的和异常高的质量。 质量，适合出版，提交NDAR，并立即由其他科学家使用。关键人员将 提供数学分析，生物统计学，软件工程和数据处理方面的专业知识， 实现每个项目的具体目标。将提供共享设施和基础设施， 每个项目的数据管理和分析需求，包括中央超级计算设施，本地 工作站和一套为每个项目所需的数据处理而定制的软件工具。数据 管理将集中在一个共同的数据服务器上使用马库斯数据交换（DEX），一个自定义的- 委托Prometheus Research LLC设计的RexDB®数据库，专门用于处理大容量 临床、行为和实验数据集，以及它们到NDAR的传输（请参见参考资料& 环境，第7.4.2和7.4.4节）。

PROJECT SUMMARY The objective of the Emory ACE Data Management & Analysis Core is to create an optimal scientific and technical environment for creating growth charts of social engagement from densely-sampled longitudinal data sets co-registered across multiple domains in order to explore cycles of social contingency in autism and pivotal transitions in development, a key aim of Projects I-V as well as the whole program project. To accomplish this goal, the Core will provide shared resources, facilities and expertise for data collection, processing, analysis, storage and retrieval to serve the entire program project, as well as acting as a common repository for sharing data between individual projects and transmitting results to NDAR. The specific aims of the Core are: (1) Data Management: to meet the uniquely challenging data processing, management, storage and transmission needs of the entire program project; (2) Data Analysis: to provide a common methodological framework and shared computational infrastructure for carrying out state-of-the-art developmental profiling and statistical analysis of experimental measures collected across Projects I-V; (3) Training and Reliability: to provide common training in all of the novel data analysis techniques employed across projects, and to ensure that those techniques are deployed consistently and reliably across projects, using appropriate procedures for data management; and (4) Quality Control: to ensure that all data arising from the program project are of uniformly and exceptionally high quality, suitable for publication, submission to NDAR, and immediate use by other scientists. Key personnel will provide expertise in mathematical analysis, biostatistics, software engineering, and data processing needed to achieve the specific aims of each project. Shared facilities and infrastructure will be made available to support the data management and analysis needs of each project, including a central supercomputing facility, local workstations, and a suite of software tools customized for the data processing required in each project. Data management will be centralized on a common data server using the Marcus Data Exchange (DEX), a custom- designed RexDB® database commissioned from Prometheus Research LLC specifically to handle large-volume clinical, behavioral, and experimental data sets, and their transmission to NDAR (please see Resources & Environment, Sections 7.4.2 and 7.4.4).