ArticleExperimental neurology2025
Data reporting quality and semantic interoperability increase with community-based data elements (CoDEs). Analysis of the open data commons for spinal cord injury (ODC-SCI).
Article in Experimental neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Funding Distributions, Trends, Gaps, and Policy Implications for Spinal Cord Injury Research: A Systematic Analysis of U.S. Federal Funds.Journal of neurotrauma · 2025Article
- A Community Effort to Develop Common Data Elements for Pre-Clinical Spinal Cord Injury Research.Neurotrauma reports · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Data interoperability is crucial for effectively combining data for scientific inquiry. To facilitate interoperability, data standards such as a common definition of variables are often developed. The Open Data Commons for Spinal Cord Injury (odc-sci.org) has established an initial set of community-based data elements (CoDEs)-a minimal set of variables for sharing-to promote data interoperability in SCI research, aligning with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. We sought to understand the use of CoDEs by the SCI community to inform current standards adherence and future standards development. We systematically analyzed 39 public datasets in relation to 17 required CoDEs and found variations between reported data and the structure specified by the CoDEs. Overall, we found that the enforcement of data standards improved reporting rates of CoDEs variables. Notably, different variables were found to require different levels of curation to ensure semantic equivalence among datasets. We also uncovered specific reporting habits of researchers such as formatting and naming patterns. A need for different data standards based on the nature of the study (e.g., human study, derivative study) was realized alongside a detailed list of issues that should be addressed when implementing such standards. Among the various approaches to developing data standards, ODC-SCI adopted a semi-formal approach by creating standards that are easy to adopt by the user. Our data-driven evaluation of actual reporting behavior shows that this flexibility can lead to subsequent problems in harmonization. This study serves as a baseline analysis of reporting behaviors for shaping and facilitating data standards.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.