# Community-Driven Sensor Metadata Ecosystem for Exposure Health

> **NIH NIH R24** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $615,941

## Abstract

PROJECT SUMMARY ABSTRACT
Environmental exposures heavily influence human health. To gain more precise insight into environmental
exposures' effects on health, scientists must integrate and assimilate sensor data and other types of research
data across domains and varied temporal and spatial scales. However, we lack informatics tools that enable
researchers to share, find, assess, and re-use environmental data sources. The central problem is the lack of
associated metadata that enables appropriate use and re-use. There is a lack of consensus on metadata
standards and conceptual models representing the exposure domain. Investigators and curators of real-world
data collections are often not incentivized or responsible for metadata discovery for data re-use. Moreover, we
lack accessible tools that enable scientists to discover, harmonize, store, and publish metadata. In prior work,
we developed the Exposure Health Informatics Ecosystem (EHIE), a scalable, standards-based, open-source
informatics infrastructure. EHIE supports semantically consistent, metadata-driven, event-based management
of exposure data for research. Here, we propose to leverage our expertise in metadata and event-based
modeling to advance methods for exposure health research entailing sensors. In aim 1, we will develop a
logical model for representing diverse types of sensor metadata, and in doing so, discover and harmonize
sensor and device metadata in a community-driven approach. In aim 2, we design and evaluate a user-facing
metadata repository that will encompass a library of data, sensors/ devices, and interfaces that support
metadata submission and browsing. In aim 3, we will develop specifications, logical models, and the functions
needed to transform any exposure health data into an event-based format, enhanced with spatial and temporal
coordinates. In aim 4, we will develop prototype workflows that research teams can use as models for using
the tools we create to generated metadata-enhanced, semantically consistent exposure health data. Across
these four aims, we engage the environmental exposure health research community through an expert panel,
user-centered design, public comment, and a communications plan. This effort builds upon prior research and
development efforts of an experienced informatics team in conjunction with the University of Utah's Center of
Excellence in Exposure Health Informatics. The expected outcome is the development of community-driven,
shared, and generalizable tools for metadata and data management, supporting reproducible environmental
exposure health research.

## Key facts

- **NIH application ID:** 10840116
- **Project number:** 1R24ES036134-01
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** MOLLIE R. CUMMINS
- **Activity code:** R24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $615,941
- **Award type:** 1
- **Project period:** 2024-05-24 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10840116

## Citation

> US National Institutes of Health, RePORTER application 10840116, Community-Driven Sensor Metadata Ecosystem for Exposure Health (1R24ES036134-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10840116. Licensed CC0.

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