# Data Management and Analysis Core (DMAC)

> **NIH NIH P42** · UNIVERSITY OF RHODE ISLAND · 2022 · $230,583

## Abstract

PROJECT SUMMARY/ABSTRACT – DATA MANAGEMENT AND ANALYSIS CORE (DMAC)
To understand the link between PFAS exposure and disease, there is a need for data integration from a broad
range of scientific disciplines and for researchers to acknowledge the importance of the entire lifecycle of the
data in a context beyond their immediate research objective. The long-term goal is to establish a data science
infrastructure that promotes best practice, i.e., high-quality data that are Findable, Accessible, Interoperable, and
Reusable (FAIR), and that will be easily applicable to other interdisciplinary team projects. DMAC’s overall
objective is to work closely with all STEEP project members and equip them with low-cost, user-friendly, FAIR-
integrated processes, as well as cutting-edge statistical and computing methods. Guided by the team’s
experience, DMAC will pursue four specific aims: (i) develop, coordinate, and monitor a user-friendly, easily-
accessible infrastructure and processes for creating, storing, and sharing data and metadata, irrespective of
size, both internally and publicly, (ii) address metadata needs across all STEEP research data products, (iii)
provide integrative methodological and computational support, as well as develop mission-oriented methods,
and (iv) develop standards for and provide data quality assurance and quality control (QA/QC) across STEEP
projects. The approach is innovative because it departs from the status quo by providing: (i) an easy-to-
implement, modern, and integrative data management infrastructure that is compliant with all FAIR principles
and QA/QC, (ii) cutting-edge statistical methods (e.g., causal inference, Bayesian, and time series models) to
draw mathematically-precise inferences from complex data structures (e.g., non-randomized, longitudinal), and
(iii) high-performance computing resources. The proposed research is significant because it is expected to
advance and expand the use of FAIR-compliant research in the field of environmental health. Ultimately, such
practice has the potential to inform policy makers with precise and reliable findings and help reduce the
reproducibility crisis. STEEP’s DMAC will pursue these goals via these Specific Aims:
 Specific Aim 1: Develop and support infrastructure and processes for sharing data and metadata
 Specific Aim 2: Address metadata needs across all STEEP research data products:
 Specific Aim 3: Provide integrative statistical support
 Specific Aim 4: Develop standards for and provide data quality assurance and quality control
(QA/QC) across STEEP research projects

## Key facts

- **NIH application ID:** 10352515
- **Project number:** 2P42ES027706-06
- **Recipient organization:** UNIVERSITY OF RHODE ISLAND
- **Principal Investigator:** Harrison Dekker
- **Activity code:** P42 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $230,583
- **Award type:** 2
- **Project period:** 2017-09-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10352515

## Citation

> US National Institutes of Health, RePORTER application 10352515, Data Management and Analysis Core (DMAC) (2P42ES027706-06). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10352515. Licensed CC0.

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