Data Management and Analysis Core

项目总结 Emory ACE数据管理与分析核心的目标是创建最佳的科学和 从密集抽样的纵向数据创建社会参与度增长图表的技术环境 跨多个领域共同注册的集合，以探索自闭症和Pivotal的社会偶发循环 发展转型，这是项目I-V以及整个计划项目的一个关键目标。要做到这一点 为了实现这一目标，核心将提供共享资源、设施和专门知识，用于数据收集、处理、分析、 存储和检索，以服务于整个计划项目，并充当共享的公共存储库 在各个项目之间传输数据，并将结果传输给国家数据仓库。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：提供一个通用的方法学框架和共享 用于执行最先进的开发概况分析和统计分析的计算基础设施 跨项目I-V收集的实验措施；(3)培训和可靠性：在以下方面提供共同培训 所有跨项目采用的新颖数据分析技术，并确保这些技术 使用适当的数据管理程序，跨项目一致可靠地部署；以及(4) 质量控制：确保项目项目产生的所有数据都是一致的和异常高的 质量，适合发表，提交给ndar，并立即被其他科学家使用。关键人员将 提供所需的数学分析、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，以支持 每个项目的数据管理和分析需求，包括一个中央超级计算设施、当地 工作站，以及为每个项目所需的数据处理量身定制的一套软件工具。数据 管理将集中在使用Marcus Data Exchange(DEX)的通用数据服务器上，DEX是一种定制的- 由Prometheus Research LLC委托设计的RexDB®数据库，专门用于处理大容量数据 临床、行为和实验数据集，以及它们到NDAR的传输(请参阅参考资料& 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).