# Creating an Interoperability Data Infrastructure for Research on the Aging Lifecourse

> **NIH NIH R33** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $557,784

## Abstract

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.

## Key facts

- **NIH application ID:** 10909386
- **Project number:** 5R33AG073358-04
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** JAMES W MCNALLY
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $557,784
- **Award type:** 5
- **Project period:** 2021-09-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10909386

## Citation

> US National Institutes of Health, RePORTER application 10909386, Creating an Interoperability Data Infrastructure for Research on the Aging Lifecourse (5R33AG073358-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10909386. Licensed CC0.

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