An Interface Ontology for Alzheimer's Disease Research

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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.