# Remote Data Enclave Core

> **NIH NIH P30** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $90,772

## Abstract

Project Summary
Remote Data Enclave Core (Core E)
The Remote Data Enclave Core (Core E) will provide a Virtual Data Enclave to facilitate access
to restricted aging-related data to advance research on the demography of aging. The enclave
has two overarching goals: (1) To provide researchers around the world with efficient and secure
access to aging-related restricted-use data from NIA-funded studies; and (2) To support MiCDA
affiliates conducting aging-related projects and collaborations with restricted-use data. In the
coming cycle we will achieve these goals by (1) Expanding the MiCDA enclave's data products
and user base by: continuing partnerships with the Health and Retirement Study and Panel Study
of Income Dynamics and building new partnerships with other NIA-funded studies; building new
collaborations to make geographic data available for use with partner studies; and for local MiCDA
affiliates, expanding increasing awareness and streamlining the application process. (2) Ensuring
continued reliable system performance by: regularly reviewing, expanding and upgrading
hardware and software infrastructure; and instituting routine reporting of system performance and
capacity metrics to help avoid or swiftly diagnose and address performance problems.

## Key facts

- **NIH application ID:** 10438729
- **Project number:** 5P30AG012846-28
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Helen G Levy
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $90,772
- **Award type:** 5
- **Project period:** 1997-08-15 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10438729

## Citation

> US National Institutes of Health, RePORTER application 10438729, Remote Data Enclave Core (5P30AG012846-28). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10438729. Licensed CC0.

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