Creating an Interoperability Data Infrastructure for Research on the Aging Lifecourse

为老龄化生命历程研究创建互操作性数据基础设施

• 批准号: 10899909
• 负责人: JAMES W MCNALLY
• 金额: $ 62.99万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10899909
• 关键词: Acceleration; Address; Adoption; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Area; Atlases; Basic Science; Behavioral Research; Bibliography; COVID-19; COVID-19 complications; COVID-19 risk; Categories; Clinical; Clinical Research; Cognition; Collection; Common Data Element; Communities; Computer software; Data; Data Analyses; Data Collection; Data Files; Data Set; Discipline; Disease; Educational workshop; Extensible Markup Language; Floods; Foundations; Geography; Gerontology; Goals; Growth; Health; Health Promotion; Health behavior; Individual; Infrastructure; Interdisciplinary Study; Internet; Life Cycle Stages; Light; Longitudinal Studies; Measures; Metadata; Modeling; National Archive; Neighborhoods; Outcome; Paper; Personal Computers; Phase; Process; Public Health; Quality of life; Reproducibility; Research; Research Infrastructure; Research Personnel; Resources; Risk; Science; Services; Standardization; Structure; Technology; Training; Training and Education; United States National Institutes of Health; Wisconsin; Work; behavioral and social science; comorbidity; computerized; data integration; data interoperability; data management; data portal; data resource; data sharing; digital; improved; innovation; interoperability; novel strategies; outreach; population health; relational database; repository; social health determinants; social media; social science research; symposium; therapy development; tool; web site; webinar

Abstract: Digital data that lacks a coherent, stable, discoverable, and reproducible structure is irrelevant to the research process. Improperly or inadequately documented data files represent meaningless numbers, valueless and, ultimately, discardable. One of the significant advances over the past 20 years has been the increased use of descriptive metadata, facilitating the use and value of these data, offering greater discoverability and preliminary exploration. These changes have been part of an evolving process over the past 50 years, roughly categorized into four phases 1) The tabular paper phase, 2) The tape and mainframe phase, 3) The CD and personal computer phase, and 4) The internet distribution phase. This application argues that the broad adoption of best practices for data management, data sharing, and team science remain stalled in Phase 4. The phenomenal growth in data resources has made access to individual research data on aging simpler than ever before. Unfortunately, effective data sharing, even in light of the increased access provided by the Internet, cannot be fully realized without detailed metadata linkages that describe classes of data that share related concepts, constructs, and variables across multiple data waves or multiple related studies. This fifth phase, the interoperability phase, represents the next essential transition to support aging research for multidisciplinary team science. This application's specific goals will advance data interoperability in emerging scientific areas, facilitating team science and multidisciplinary research. By organizing independent but related data collections into a uniform structure, this application's outcomes will accelerate aging research beyond what is achievable using existing collections that treat independent data collections as unique objects. 1) Identify- The universe of aging data needs to be formally cataloged and structured at the metadata level. This process includes variable level information and concepts using a "Common Data Elements" (CDE) approach to create cross-domain XML/DDI templates to unify longitudinal studies across waves. 2) Integrate- Relate these independent longitudinal studies to each other across health thematics, including Alzheimer's disease and related dementias (ADRD), cognitions, risks associated with complications associated with COVID 19, and broader health conditions. 3) Operationalize – Make the data resources and analysis tools available to the research community and provide ongoing support and training for the interoperability portal. A DDI based Cross-Domain Integration (CDI) framework will maintain the integrated data collections, integrate the support services, bibliographic tracking, and social media outreach. The project will provide training and educational services through conference presentations, workshops, and online webinars.

抽象的： 缺乏连贯，稳定，可发现和可再现结构的数字数据与研究无关 过程。不正确或记录的数据文件表示毫无意义的数字，毫无价值， 最终，可抛弃。过去20年中的重大进展之一是增加使用 描述性元数据，支持这些数据的使用和价值，提供更大的发现性和 初步探索。这些变化一直是过去50年中不断发展的过程的一部分，大致 分为四个阶段1）表格阶段，2）胶带和大型机阶段，3）CD和 个人计算机阶段和4）互联网分销阶段。该应用程序认为广泛 在第4阶段中采用最佳实践，数据共享和团队科学的最佳实践仍然停滞不前。 数据资源的惊人增长使您可以访问有关衰老的单个研究数据，而不是 以前。不幸的是，即使鉴于访问的增加，有效的数据共享 没有详细的元数据链接描述共享的数据类别的互联网，无法完全实现 跨多个数据波或多个相关研究的相关概念，构造和变量。第五 阶段，互操作性阶段，代表了支持老化研究的下一个基本过渡 多学科团队科学。该应用程序的特定目标将提高新兴的数据互操作性 科学领域，支持团队科学和多学科研究。通过组织独立但相关 数据收集到统一结构，此应用程序的结果将加速衰老研究 使用现有集合将独立数据收集视为独特对象的现有集合可以实现。 1） 识别 - 老化数据的宇宙需要在元数据级别正式分类和结构。这 过程包括使用“常见数据元素”（CDE）方法的可变级别信息和概念 创建跨域XML/DDI模板，以统一跨波的纵向研究。 2）将这些融合在一起 跨健康主题，包括阿尔茨海默氏病和 相关痴呆症（ADRD），认知，与Covid 19相关的并发症相关的风险， 更广泛的健康状况。 3）操作 - 使数据资源和分析工具可用于 研究社区，并为互操作性门户提供持续的支持和培训。基于DDI 跨域集成（CDI）框架将维护集成数据收集，集成支持 服务，书目跟踪和社交媒体外展。该项目将提供培训和教育 通过会议演示，研讨会和在线网络研讨会的服务。