# Core B:  Data Management Core

> **NIH NIH U19** · WASHINGTON UNIVERSITY · 2024 · $2,366,861

## Abstract

ABSTRACT
Core B: Data Management Core
Washington University (Miller, J. Philip)
The overarching objective of the Data Management Core-B is to serve as the central hub for the analysis,
sharing and harmonization of data across the Respirovirus, Rubulavirus, Peribunyavirus and Phenuivirus-
ReVAMPP (R2P2-ReVAMPP) center at Washington University. The core will work directly with Projects 1-4
and Scientific Cores C-E of the R2P2-ReVAMPP center to provide the expertise necessary to ensure the
effective collection, sharing, storage, harmonization, and analysis of data sets and to enable dissemination of
information broadly within the center. We aim to reimagine how a Data Management Core operates by leveraging
the power of cloud technology and metadata-based ontologies. Traditional models of data cores tend to
compartmentalize information into separate databases for each project or core, which are then merged for
specific analyses when needed. This approach, while functional, can lead to inefficiencies, discrepancies
between datasets, and an inability to harness the full potential of interconnected datasets. Our innovative
proposal involves the use of WUVAX, a modern, cloud-based system. Instead of separate databases, all data in
WUVAX is integrated, updated in real-time, and made directly accessible to investigators.
A simplified user interface where data and progress for Projects 1-4 and Cores C-E can be visualized and
assessed in real time will inform investigators of the progress of research within the Center. Metrics will be
displayed in a user-friendly manner involving graphs, charts, tables and project time-lines. We will develop and
implement a library on the WUVAX application where documentation, manuscript drafts, Center policies, reports,
datasets, etc. will be stored. The Core B team is skilled in various data analysis methods, including basic
univariate analyses (e.g., t-tests, chi-square tests), advanced multivariable techniques (e.g., generalized linear
models), and machine-learning approaches (e.g., classification trees, random forests). Core B will apply these
skills to offer analytical support to the Projects and Cores. The Data Management Core-B will also interface
directly with the overall ReVAMPP network Coordinating and Data Sharing Center (ReVAMPP CDSC) so that
data is acquired and disseminated within the overall network, its partners, and the scientific community.

## Key facts

- **NIH application ID:** 10863693
- **Project number:** 1U19AI181984-01
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** J. Philip MILLER
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $2,366,861
- **Award type:** 1
- **Project period:** 2024-09-11 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10863693

## Citation

> US National Institutes of Health, RePORTER application 10863693, Core B:  Data Management Core (1U19AI181984-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10863693. Licensed CC0.

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