# Data Management and Analysis Core

> **NIH ES P42** · UNIVERSITY OF ARIZONA · 2026 · $406,835

## Abstract

PROJECT SUMMARY (Data Management and Analysis Core: Lemos, Swetnam, Merchant) 
The University of Arizona Superfund Research Program (UA SRP) will generate volumes and types of data that 
are not manageable in typical laboratory settings. The Data Management and Analysis Core (DMAC) will function 
as the primary service for UA SRP data management and analysis of large biological, geophysical, and chemical 
datasets, including but not limited to bulk and single cell RNA sequencing, geospatial coordinates and 
geochemical composition, analytical chemistry, and imaging. DMAC enables investigators by performing three 
core functions: (i) DMAC will lead the housing of all data in an easy-to-access data repository system: CyVerse. 
Cyverse is a computational infrastructure consisting of hardware, software, and personnel that are designed to 
handle huge datasets and complex analyses, and is maintained at the University of Arizona. DMAC will utilize a 
reference implementation (RI) that divides data into five different levels for easy data sharing, processing, and 
analyzing. Lowest levels (level 1) will be raw data, while higher levels (level 5) will be file formats utilizable in 
graphics visualizations. DMAC will support these processes with help from on-staff data analysts and 
bioinformaticians as well as CyVerse programmers who can devise analysis strategies for individual 
investigators. In addition to data storage, DMAC will orchestrate sample management using Fulcrum software. 
Fulcrum allows barcoding, global positioning, and annotation of biological samples in an easy-to-use application 
available on both traditional workstations and mobile platforms. (ii) Beyond data and sample management, 
DMAC will perform both standard and custom computational processing and analyses of data. In conjunction 
with UA SRP investigators, DMAC will apply traditional algorithms, or develop novel algorithms as needed, to 
identify signatures for the different data types collected. 

## Key facts

- **NIH application ID:** 11375951
- **Project number:** 5P42ES004940-37
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** Bernardo  Lemos
- **Activity code:** P42 (R01, R21, SBIR, etc.)
- **Funding institute:** ES
- **Fiscal year:** 2026
- **Award amount:** $406,835
- **Award type:** 5
- **Project period:** 1997-04-01T00:00:00 → 2030-01-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11375951

## Citation

> US National Institutes of Health, RePORTER application 11375951, Data Management and Analysis Core (5P42ES004940-37). Retrieved via AI Analytics 2026-06-30 from https://api.ai-analytics.org/grant/nih/11375951. Licensed CC0.

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