# Data Science Core

> **NIH NIH U19** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $347,800

## Abstract

Core 1. Abstract
 Data Science Core
 The Data Science Core aims to streamline TeamBCP's data management and sharing by overhauling its
server infrastructure and data conversion pipelines. Recognizing the existing barriers to data sharing and re-use,
the Core is committed to organize datasets according to established guidelines for public dissemination. Our
approach will ensure that datasets adhere to these norms and standards from the outset, as data are stored and
aggregated. Specialized data repositories will be established at each performance site, integrated with existing
infrastructures, and optimized for quick database queries and data analysis. Data conversion and processing
pipelines will be developed to align with researchers' workflows, facilitating data transfer to local repositories and
supporting collaborative efforts. Publication to online data repositories will be greatly facilitated by the integrated
conversion to standard formats. Tools for data analysis will also be packaged and distributed for ease of use and
reproducibility. Additionally, a secure web portal will be introduced to provide centralized access to all TeamBCP
data, offering functionalities for data visualization and annotation. Through these initiatives, the Core aims to
facilitate research, collaboration, and public data sharing.

## Key facts

- **NIH application ID:** 10930313
- **Project number:** 1U19NS137920-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Vincent Prevosto
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $347,800
- **Award type:** 1
- **Project period:** 2024-08-15 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10930313

## Citation

> US National Institutes of Health, RePORTER application 10930313, Data Science Core (1U19NS137920-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10930313. Licensed CC0.

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