ReviewExperimental neurology2017
Developing a data sharing community for spinal cord injury research.
Review in Experimental neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
29 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Fighting for recovery on multiple fronts: The past, present, and future of clinical trials for spinal cord injury.Frontiers in cellular neuroscience · 2022Pooled it
- Reorganization of the brain in spinal cord injury: a meta-analysis of functional MRI studies.Neuroradiology · 2019Pooled it
- Outcome heterogeneity and bias in acute experimental spinal cord injury: A meta-analysis.Neurology · 2019Pooled it
- 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).Experimental neurology · 2025Article
- A Community Effort to Develop Common Data Elements for Pre-Clinical Spinal Cord Injury Research.Neurotrauma reports · 2025Review
- Construction of a Searchable Database for Gene Expression Changes in Spinal Cord Injury Experiments.Journal of neurotrauma · 2024Article
- NSF DARE-transforming modeling in neurorehabilitation: perspectives and opportunities from US funding agencies.Journal of neuroengineering and rehabilitation · 2024Article
- Data and subject heterogeneity and data sharing: keys to translational success in spinal cord injury research?Neural regeneration research · 2023Article
- Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan.PLoS computational biology · 2022Article
- Data sharing across osteoarthritis research groups and disciplines: Opportunities and challenges.Osteoarthritis and cartilage open · 2022Article
- Harmonization-Information Trade-Offs for Sharing Individual Participant Data in Biomedicine.Harvard data science review · 2022Article
- Reflections on Data Sharing Practices in Spinal Cord Injury Research.Neuroinformatics · 2022Article
- Empowering Data Sharing and Analytics through the Open Data Commons for Traumatic Brain Injury Research.Neurotrauma reports · 2022Article
- Excavating FAIR Data: the Case of the Multicenter Animal Spinal Cord Injury Study (MASCIS), Blood Pressure, and Neuro-Recovery.Neuroinformatics · 2022Article
- Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project.Frontiers in neuroinformatics · 2022Article
- Review
- Reproducible analysis of disease space via principal components using the novel R package syndRomics.eLife · 2021Article
- The Life of a Trailing Spouse.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- The neuroanatomical-functional paradox in spinal cord injury.Nature reviews. Neurology · 2021Review
- Data Dissemination: Shortening the Long Tail of Traumatic Brain Injury Dark Data.Journal of neurotrauma · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
The rapid growth in data sharing presents new opportunities across the spectrum of biomedical research. Global efforts are underway to develop practical guidance for implementation of data sharing and open data resources. These include the recent recommendation of 'FAIR Data Principles', which assert that if data is to have broad scientific value, then digital representations of that data should be Findable, Accessible, Interoperable and Reusable (FAIR). The spinal cord injury (SCI) research field has a long history of collaborative initiatives that include sharing of preclinical research models and outcome measures. In addition, new tools and resources are being developed by the SCI research community to enhance opportunities for data sharing and access. With this in mind, the National Institute of Neurological Disorders and Stroke (NINDS) at the National Institutes of Health (NIH) hosted a workshop on October 5-6, 2016 in Bethesda, MD, in collaboration with the Open Data Commons for Spinal Cord Injury (ODC-SCI) titled "Preclinical SCI Data: Creating a FAIR Share Community". Workshop invitees were nominated by the workshop steering committee (co-chairs: ARF and VPL; members: AC, KDA, MSB, KF, LBJ, PGP, JMS), to bring together junior and senior level experts including preclinical and basic SCI researchers from academia and industry, data science and bioinformatics experts, investigators with expertise in other neurological disease fields, clinical researchers, members of the SCI community, and program staff representing federal and private funding agencies. The workshop and ODC-SCI efforts were sponsored by the International Spinal Research Trust (ISRT), the Rick Hansen Institute, Wings for Life, the Craig H. Neilsen Foundation and NINDS. The number of attendees was limited to ensure active participation and feedback in small groups. The goals were to examine the current landscape for data sharing in SCI research and provide a path to its future. Below are highlights from the workshop, including perspectives on the value of data sharing in SCI research, workshop participant perspectives and concerns, descriptions of existing resources and actionable directions for further engaging the SCI research community in a model that may be applicable to many other areas of neuroscience. This manuscript is intended to share these initial findings with the broader research community, and to provide talking points for continued feedback from the SCI field, as it continues to move forward in the age of data sharing.
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What OpenQuestion holds
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.