An Interface Ontology for Alzheimer's Disease Research

项目摘要 阿尔茨海默病（AD）研究中的一个关键障碍是传统的数据访问工作流， 在访问患者数据之前进行假设，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接口允许研究人员简单地探索 数据并构建查询，而无需用户理解数据是如何存储的。但这种 界面还没有达到接近消费者网站的水平的可用性。的 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）。现有的广告相关元数据标准化工作包括： 阿尔茨海默病研究本体（CADRO），由国家老龄化研究所和 阿尔茨海默氏症协会，使整合和比较分析AD研究组合的战略 规划和协调。阿尔茨海默病治疗领域用户指南（TAUG-Alzheimer's） 由临床数据交换标准联盟（CDISC）和反对 主要疾病（CAMD），以提高效率和学习的临床试验在AD。虽然他们是 收集和管理数据的重要元数据资源，这些现有AD术语和数据 标准没有被设计成可直接用于开发数据探索，因此是不够的 AD研究的工具和界面。我们建议开发一个新的界面本体论用于广告研究 （ADIO）通过两个特定目标支持基于Web的数据分面探索。在目标1中，我们将开发 ADIO和模型是AD相关生物医学概念的全面集合，将直接用于 推动基于网络的数据探索工具。在目标2中，我们将开发ADIO-DE，一个直接适用的，基于Web的 使用国家阿尔茨海默病协调中心的AD队列发现和测试ADIO-DE的数据探索工具 中心（NACC）和阿尔茨海默病神经成像倡议（ADNI）数据集。预期结果 这项研究将在基于网络的工具方面开辟新天地，并利用现有数据资源来加速AD research.我们期望ADIO、ADIO-DE及其未来版本成为AD的宝贵资源 研究社区。本研究的长期目标是为NACC、ADNI创建数据探索系统 和其他相关的广告数据资源，通过数据科学创新， 生成数据交互模式。

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.