# Data Science Core

> **NIH NIH U19** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2022 · $116,401

## Abstract

Biomedical research has experienced a crisis of reproducibility, exacerbated by lack of coordination between
research groups, weak study designs, opaque algorithms, and an unwillingness to share the fruits of research
efforts. But recent years have seen the beginning of a push to solve this crisis, with a focus on integration
across labs, standardization, rigorous statistical analysis, open source code, and the sharing of data and
methods. This proposal aims to “Crack the Olfactory Code”, a far-reaching goal that will require a firm
commitment to rigorous, open science principles. The Data Science Core (DSC) for this proposal reflects a
plan to meet this commitment in three major ways: (1) The DSC will tightly coordinate the integration of data
across the proposal’s five scientific projects, utilizing standards and adopting technology for total reproducibility
of all findings, as well as ensuring that all research outputs will be made comprehensively and intelligibly
available to the public; (2) The DSC will work with project leaders to optimize data collection decisions using
statistical models, saving time and money while increasing scientific inference; (3) The DSC will standardize
odorant stimuli across projects and create a service for pushing this standard into the larger research
community, ensuring that future research efforts can be directly informed by our efforts and can inform each
other.

## Key facts

- **NIH application ID:** 10413204
- **Project number:** 5U19NS112953-04
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Richard C Gerkin
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $116,401
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10413204

## Citation

> US National Institutes of Health, RePORTER application 10413204, Data Science Core (5U19NS112953-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10413204. Licensed CC0.

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