Clinical and Outcome Data
Headache frequency, intensity, disability indices, medication use, and follow-up outcomes with clear variable definitions.
Data and Reproducibility Policy
Data Archiving Permissions
Data Archiving Permissions
Journal of Migraine Management
Guidance on sharing migraine research data responsibly, with reproducibility, privacy, and policy compliance in balance.
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Data Principles
Archiving for Reproducibility and Long-Term Access
Data transparency improves confidence in migraine evidence and supports secondary analysis across care settings.
Journal of Migraine Management encourages authors to archive datasets, protocols, and analytic code whenever legal and ethical constraints allow.
Robust archiving helps clinicians, guideline teams, and researchers validate findings, compare treatment performance, and reuse data for updated evidence synthesis.
Data sharing plans should be prepared before submission and reflected in the manuscript Data Availability Statement.
Patient-Reported Measures
Instrument-based responses and scoring logic for quality-of-life and symptom burden analysis.
Imaging and Biomarker Assets
Curated files and metadata for neuroimaging or biomarker studies with versioned processing notes.
Code and Statistical Scripts
Scripts for preprocessing, modeling, and sensitivity checks with dependency documentation.
Repository Selection
Where to Store Data and Supplementary Files
Choose repositories that provide persistent identifiers, access controls, and durable hosting.
- Use recognized repositories such as Zenodo, Figshare, OSF, Dryad, or approved institutional repositories.
- Assign persistent identifiers to shared datasets whenever supported.
- Include version details and update history for revised datasets.
- Provide machine-readable metadata and clear file naming standards.
- Link repositories directly in manuscript data statements.
For sensitive clinical datasets, controlled access models are acceptable. In such cases, explain who can request access, what documentation is required, and expected response timelines.
If embargo periods apply, state embargo end date and interim access conditions so readers understand future availability.
Privacy and Governance
Handling Sensitive Information Responsibly
Archiving requirements must be balanced with participant privacy, contractual obligations, and legal frameworks.
De-identification
Remove direct identifiers and assess re-identification risk before any external release.
Consent Compatibility
Ensure data sharing permissions align with participant consent terms and institutional policy.
Third-Party Restrictions
Document licensing limits for proprietary instruments, datasets, or software outputs.
Data Use Conditions
State permitted uses, prohibited uses, and citation expectations for shared resources.
Authors remain responsible for confirming that data release decisions comply with local regulations and ethics approvals.
Submission Requirements
What to Include in the Manuscript
Every manuscript should include a data availability statement that is specific and verifiable.
- Repository name and persistent link or identifier.
- Description of data files and variable dictionaries.
- Access status: open, restricted, embargoed, or unavailable with reason.
- Contact pathway for controlled-access requests.
- Code availability status and software dependency notes.
Editorial check: Data statements are reviewed during triage. Vague statements may trigger a technical return before peer review.
Data statements should identify not only repository location but also variable definitions and file structure context. This improves practical reusability for independent analysts and evidence reviewers.
Where controlled access is required, describe request governance, review criteria, and expected response timing so potential users understand feasibility before requesting sensitive datasets.
Version tracking is especially important when datasets evolve after initial publication. Authors should document update rationale and maintain continuity between manuscript analyses and archived files.
Code availability notes should include execution environment details to reduce ambiguity in reproducibility attempts. Even brief environment notes can materially improve secondary validation workflows.
Clinical datasets require careful anonymization with documented risk controls to maintain participant privacy while preserving analytical utility. Balanced governance strengthens trust in shared evidence.
Data archiving planning is most effective when coordinated before submission rather than after acceptance. Early planning reduces policy-related revisions and accelerates publication readiness.
Data statements should identify not only repository location but also variable definitions and file structure context. This improves practical reusability for independent analysts and evidence reviewers.
Where controlled access is required, describe request governance, review criteria, and expected response timing so potential users understand feasibility before requesting sensitive datasets.
Version tracking is especially important when datasets evolve after initial publication. Authors should document update rationale and maintain continuity between manuscript analyses and archived files.
Code availability notes should include execution environment details to reduce ambiguity in reproducibility attempts. Even brief environment notes can materially improve secondary validation workflows.
Plan Data Sharing Before Submission
Use clear repository and access statements so reviewers and readers can verify your evidence responsibly.
Editorial support: [email protected]
