# An Interface Ontology for Alzheimer's Disease Research

> **NIH NIH R21** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2020 · $234,000

## Abstract

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.

## Key facts

- **NIH application ID:** 10042812
- **Project number:** 1R21AG068994-01
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** Licong Cui
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $234,000
- **Award type:** 1
- **Project period:** 2020-09-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10042812

## Citation

> US National Institutes of Health, RePORTER application 10042812, An Interface Ontology for Alzheimer's Disease Research (1R21AG068994-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10042812. Licensed CC0.

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