An Interface Ontology for Alzheimer's Disease Research

阿尔茨海默病研究的界面本体

• 批准号: 10042812
• 负责人: Licong Cui
• 金额: $ 23.4万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10042812
• 关键词: Address; Affect; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease related dementia; Alzheimer' s disease therapeutic; American; Area; Automobile Driving; Clinical Data; Clinical Research; Clinical Trials; Cohort Studies; Collection; Common Data Element; Communities; Data; Data Element; Data Science; Data Set; Development; Disease; Evaluation; Funding; Future; Generations; Goals; Grain; Growth; Infrastructure; Lead; Learning; Memory impairment; Metadata; Modality; Modeling; National Institute on Aging; Neurologic; Online Systems; Ontology; Patients; Performance; Privacy; Process; Public Health; Reporting; Reproducibility; Research; Research Personnel; Resources; Semantics; Sleep; Software Tools; Standardization; Strategic Planning; Subgroup; System; Terminology; Testing; Translations; United States National Institutes of Health; Web Ontology Language; Work; base; case control; cohort; comparative; daily functioning; data access; data exploration; data integration; data management; data resource; data sharing; data sharing networks; data standards; experience; human data; human old age (65+); improved; informatics tool; innovation; interoperability; nervous system disorder; neuroimaging; novel; prevent; query tools; success; tool; usability; web site; web-based tool

PROJECT SUMMARY A key barrier in Alzheimer’s disease (AD) research is the traditional data access workflow that requires a hypothesis prior to accessing patient data, rather than a workflow that begins with data exploration while protecting privacy. Existing data access interfaces for AD data resources allow researchers to simply explore data and build queries without the need for the user to understand how the data is stored. However, such interfaces have not achieved usability approaching the levels of those for consumer websites. The development of effective tools to support AD research data exploration requires standardized AD terminologies and data standards (or metadata). Existing efforts to standardize AD-related metadata include the Common Alzheimer’s Disease Research Ontology (CADRO), developed by the National Institute on Aging and the Alzheimer’s Association, to enable integration and comparative analysis of AD research portfolios for strategic planning and coordination. The Alzheimer's Disease Therapeutic Area User Guide (TAUG-Alzheimer's), has been developed by the Clinical Data Interchange Standards Consortium (CDISC) and the Coalition Against Major Diseases (CAMD), to improve the efficiency and learning from clinical trials in AD. Although they are important metadata resources for collecting and managing data, these existing AD terminologies and data standards are not designed, and thus are not sufficient, to be directly usable for developing data exploration tools and interfaces for AD research. We propose to develop a novel Interface Ontology for AD research (ADIO) to support web-based data faceted exploration through two Specific Aims. In Aim 1 we will develop ADIO and model a comprehensive collection of AD-related biomedical concepts which will be directly used for driving web-based data exploration tools. In Aim 2 we will develop ADIO-DE, a directly applicable, web-based data exploration tool for AD cohort discovery and test ADIO-DE using the National Alzheimer’s Coordinating Center (NACC) and Alzheimer's Disease Neuroimaging Initiative (ADNI) datasets. Anticipated results from this study will break new ground in web-based tools and capitalize on available data resources to accelerate AD research. We expect ADIO, ADIO-DE and their future versions to become an invaluable resource for the AD research community. The long-term goal of this study is to create data exploration systems for NACC, ADNI and other related AD data resources through data science innovations to transform user experience with a new generation of data interaction modalities.

项目摘要 阿尔茨海默氏病（AD）研究的关键障碍是传统的数据访问工作流程，需要 在访问患者数据之前的假设，而不是从数据探索开始的工作流程 保护隐私。 AD数据资源的现有数据访问界面使研究人员可以简单地探索 数据并构建查询，而无需用户了解数据的存储方式。但是，这样 界面尚未实现可用性，即接近消费者网站的水平。这 开发支持AD研究数据探索的有效工具需要标准化的AD术语 和数据标准（或元数据）。现有的标准化与广告相关的元数据的努力包括常见 阿尔茨海默氏病研究本体论（CADRO），由美国国家老化研究所和 阿尔茨海默氏症协会，以实现AD研究组合的整合和比较分析以进行战略 计划与协调。阿尔茨海默氏病治疗区用户指南（塔格 - 阿尔茨海默氏症）已有 我们是由临床数据互换标准财团（CDISC）和反对联盟开发的 主要疾病（CAMD），以提高AD临床试验的效率和学习。虽然是 这些现有的AD术语和数据的重要元数据资源用于收集和管理数据 标准不是设计的，因此不足以直接用于开发数据探索 广告研究的工具和接口。我们建议开发一个新颖的界面本体，以进行广告研究 （ADIO）通过两个具体目标来支持基于Web的数据。在目标1中，我们将发展 ADIO和模拟与广告相关的生物医学概念的全面集合，将直接用于 驱动基于网络的数据探索工具。在AIM 2中，我们将开发ADIO-DE，这是一个直接适用的，基于网络的 使用国家阿尔茨海默氏症协调的数据探索工具用于AD队列发现和测试ADIO-DE 中心（NACC）和阿尔茨海默氏病神经影像倡议（ADNI）数据集。预期的结果 研究将在基于Web的工具中打破新的基础，并利用可用的数据资源以加速AD 研究。我们希望Adio，Adio-De及其未来版本将成为广告的宝贵资源 研究社区。这项研究的长期目标是为NACC创建数据勘探系统 和其他相关的广告数据资源通过数据科学创新，以新的方式改变用户体验 生成数据相互作用方式。