# Enhancing the Pan-Neurotrauma Data Commons (PANORAUMA) to a complete open data science tool by FAIR APIs

> **NIH NIH U24** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $239,625

## Abstract

Project Summary
Neurotrauma (trauma to the spinal cord and brain) affects over 2.5 million individuals in the US, with an annual
economic impact of $80 billion in medical and socioeconomic costs. Despite improved patient management in
the last decades, there are limited viable options to promote neurological recovery. Spinal cord injury (SCI) and
traumatic brain injury (TBI) result in multifaceted syndromes spanning heterogeneous data sources and multiple
scales of analysis. In addition, these injuries often occur at various sites within the central nervous system, with
graded severities producing heterogeneous injuries with diverse outcome trajectories. Making sense of this
complexity requires pooling data across multiple injury severities, types, and scales of analysis ranging from
molecular, anatomical, physiological, and behavioral levels. Large-scale data resources and big-data tools have
the potential to help. By pooling and harmonizing diverse data at the individual level, it becomes possible to
make neurotrauma data “Findable, Accessible, Interoperable, and Reusable” (FAIR). FAIR neurotrauma data
can be harnessed using modern data workflows and analytics, directing novel discovery and accelerating
translation. Moreover, FAIR data can set the stage for widespread adoption of artificial intelligence (AI) and
machine learning (ML), and it is at the core of NIH Strategic Plan for Data Science and AI/ML-readiness initiatives
like Bridge2A1 and AIM-AHEAD.
Researchers and data scientists can use FAIR neurotrauma data to drive novel discoveries and build robust
reproducibility and translation tools, such as data processing software and new analytical workflows and
pipelines. The overarching objective of the Pan-Neurotrauma data commons parent project is to build a Pan-
Neurotrauma (PANORAUMA) data commons infrastructure. The award aims at improving the efficiency, quality,
and sustainability of the community-driven Open Data Commons for Spinal Cord Injury (odc-sci) and Traumatic
Brain Injury (odc-tbi) by centralizing their operations and governance. The NOSI (NOT-OD-22-068) for this
supplement provides an opportunity for “improving the quality and sustainability of research software from a
software engineering perspective.” The supplement is vital for PANORAUMA sustainability and the expansion
of the community of users to include research data scientists and research software developers in response to
NIH’s strategic plan for data science which states that “accessible, well-organized, secure, and efficiently
operated data resources are critical to modern scientific inquiry.” For this supplement, we propose to: 1) develop
the Application Programming Interface (API) of PANORAUMA to better support data science activities in the
cloud and optimize reusability, interoperability, and sustainability of data pipelines; 2) incorporate the SmartAPI
FAIR standards to maximize the API’s FAIRness and documentation; 3) enhance the PANORAUMA-API
interface with ...

## Key facts

- **NIH application ID:** 10608657
- **Project number:** 3U24NS122732-02S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** ADAM R FERGUSON
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $239,625
- **Award type:** 3
- **Project period:** 2021-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10608657

## Citation

> US National Institutes of Health, RePORTER application 10608657, Enhancing the Pan-Neurotrauma Data Commons (PANORAUMA) to a complete open data science tool by FAIR APIs (3U24NS122732-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10608657. Licensed CC0.

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