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The Spinal Cord

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Related Experiment Video

Updated: Mar 1, 2026

Author Spotlight: Insight Into Innovations in Spinal Cord Injury Research

Author Spotlight: Insight Into Innovations in Spinal Cord Injury Research

Published on: January 19, 2024

Developing a data sharing community for spinal cord injury research.

Alison Callahan¹, Kim D Anderson², Michael S Beattie³

¹Stanford Center for Biomedical Informatics Research, Stanford University, Stanford 94305, CA, USA.

Experimental Neurology

|June 4, 2017

Summary

This summary is machine-generated.

Implementing FAIR Data Principles is crucial for advancing biomedical research. This workshop focused on improving data sharing within the spinal cord injury (SCI) research community, fostering a FAIR share environment.

Keywords:

FAIR data principles Informatics Neuroscience Open Data Commons Reproducibility Workshop proceedings

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Area of Science:

Biomedical Research
Neuroscience
Data Science

Background:

The biomedical field is experiencing rapid growth in data sharing, necessitating practical guidance.
The FAIR Data Principles (Findable, Accessible, Interoperable, Reusable) are essential for maximizing the scientific value of data.
The spinal cord injury (SCI) research field has a history of collaboration and is developing new tools for data sharing.

Purpose of the Study:

To examine the current landscape of data sharing in SCI research.
To identify opportunities and challenges for implementing FAIR Data Principles in SCI research.
To foster a collaborative community for preclinical SCI data sharing.

Main Methods:

A workshop titled "Preclinical SCI Data: Creating a FAIR Share Community" was convened by NINDS and ODC-SCI.
Workshop participants included experts from academia, industry, data science, clinical research, and funding agencies.
Discussions focused on current resources, participant concerns, and actionable directions for data sharing.

Main Results:

The workshop highlighted the value of data sharing in advancing SCI research.
Key perspectives and concerns from the SCI research community regarding data sharing were documented.
Existing resources and potential strategies for enhancing data sharing were identified.

Conclusions:

The workshop provided initial findings and talking points for the broader SCI research community.
Developing a FAIR share community is vital for the future of SCI research.
The model discussed may be applicable to other neuroscience research areas.