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A Community Effort to Develop Common Data Elements for Pre-Clinical Spinal Cord Injury Research.

Britt A Fedor1,2, Abel Torres-Espin3,4, Romana Vavrek1,2

  • 1Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, Canada.

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Developing common data elements (CDEs) is crucial for standardizing preclinical spinal cord injury (SCI) research. This initiative aims to improve data sharing and reproducibility in the field.

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Area of Science:

  • Biomedical Research
  • Neuroscience
  • Data Science

Background:

  • Scientific knowledge dissemination has historically relied on static article formats, limiting data accessibility and reuse.
  • Open science initiatives emphasize transparency, reproducibility, and replicability, necessitating improved data organization and sharing.
  • Big data, machine learning, and AI advancements require machine-readable and harmonized data for complex biological and biomedical research.

Purpose of the Study:

  • To address the challenge of organizing and describing scientific data, a skill rarely explicitly taught to researchers.
  • To establish a common language for describing and sharing preclinical spinal cord injury (SCI) research data.
  • To outline a pragmatic approach for creating Common Data Elements (CDEs) tailored for preclinical SCI research.

Main Methods:

  • Convened the "Preclinical SCI Common Data Elements (CDE) Workshop" in June 2024, in collaboration with the National Institute of Neurological Disorders and Stroke.
  • Gathered input from the SCI research community regarding data standardization needs and challenges.
  • Reviewed insights from related CDE initiatives in other research areas.

Main Results:

  • Identified the critical need for standardized data definitions and reporting structures in preclinical SCI research.
  • Highlighted the importance of machine-readable and harmonized data for leveraging advanced computational approaches.
  • Collected community input to inform the development of a practical framework for CDE creation.

Conclusions:

  • Common Data Elements (CDEs) offer a practical solution for standardizing preclinical SCI data, enhancing data sharing and interoperability.
  • The workshop proceedings and community input provide a foundation for developing a robust CDE set for SCI research.
  • Implementing CDEs will facilitate greater transparency, reproducibility, and the advancement of SCI research through improved data utilization.