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、可发现和可复制结构的数字数据与研究无关 过程。不正确或不充分记录的数据文件代表无意义的数字、无价值的， 最终，可丢弃。过去 20 年的重大进步之一是越来越多地使用 描述性元数据，促进这些数据的使用和价值，提供更大的可发现性和 初步探索。这些变化是过去 50 年不断演变的过程的一部分，大致如下： 分为四个阶段 1）表格纸阶段，2）磁带和主机阶段，3）CD 和 个人计算机阶段，以及 4) 互联网分发阶段。该申请认为，广泛的 数据管理、数据共享和团队科学最佳实践的采用在第四阶段仍然停滞不前。 数据资源的显着增长使得获取有关老龄化的个人研究数据变得更加容易 以前。不幸的是，即使考虑到数据共享提供的增加的访问，有效的数据共享 如果没有描述共享数据类别的详细元数据链接，互联网就无法完全实现 跨多个数据波或多个相关研究的相关概念、构造和变量。这第五 阶段，即互操作性阶段，代表了支持老化研究的下一个重要转变 多学科团队科学。该应用程序的具体目标将促进新兴领域的数据互操作性 科学领域，促进团队科学和多学科研究。通过组织独立但相关的 将数据收集到统一的结构中，该应用程序的成果将加速衰老研究 使用将独立数据集合视为唯一对象的现有集合可以实现什么。 1） 识别——需要在元数据级别对老化数据进行正式编目和结构化。这 流程包括使用“通用数据元素”（CDE）方法的变量级别信息和概念 创建跨域 XML/DDI 模板来统一跨波浪的纵向研究。 2）整合——将这些联系起来 跨健康主题相互独立的纵向研究，包括阿尔茨海默病和 相关痴呆症 (ADRD)、认知、与 COVID 19 相关并发症相关的风险，以及 更广泛的健康状况。 3) 操作化——使数据资源和分析工具可供使用 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）框架将维护集成的数据收集、集成支持 服务、书目跟踪和社交媒体推广。该项目将提供培训和教育 通过会议演讲、研讨会和在线网络研讨会提供服务。