Data Archiving Permissions: Etiological Diagnosis
We support transparent, responsible data sharing that strengthens etiological evidence and reproducibility.
Data Sharing for Diagnostic Confidence
Archiving data improves trust, enables reuse, and accelerates discovery of disease causes.
JED encourages authors to archive datasets, code, and supporting materials in recognized repositories whenever possible. This includes datasets used to identify causal pathways, validate diagnostic markers, or evaluate test performance. Transparent archiving supports reproducibility and strengthens the clinical relevance of etiological conclusions.
Authors must include a data availability statement describing where data can be accessed or why access is restricted. If data cannot be shared due to privacy or regulatory constraints, provide a clear rationale and a contact point for qualified requests.
Choosing the Right Archive
Use trusted repositories that provide long term access and persistent identifiers.
Recognized Repositories
Select domain specific or institutional repositories that provide stable links and strong metadata.
Persistent Identifiers
Use DOIs or accession numbers for datasets so they can be cited and tracked over time.
Controlled Access
For sensitive data, use repositories that support managed access with ethical oversight.
Metadata Quality
Provide clear descriptions, variable definitions, and protocols for reuse.
Ethics and Patient Privacy
Data sharing must comply with consent agreements and regulatory requirements.
When data include identifiable patient information, authors must anonymize records or use controlled access systems. Data from clinical studies should respect participant consent terms. If sharing is prohibited, include a statement explaining restrictions and how qualified researchers can request access through the relevant governance body.
For laboratory studies, provide raw data where feasible and document any preprocessing steps. For imaging or sequencing datasets, include file formats, software versions, and processing pipelines to support reproducibility.
What to Include
A complete data availability statement is required for every submission.
Repository Link
Provide the URL or accession number and any login requirements.
Access Conditions
Describe whether access is open, embargoed, or controlled.
Citation
Include the recommended dataset citation so readers can reference the data properly.
Long Term Preservation
Preserved datasets protect etiological evidence over time.
We recommend that datasets be retained for at least five years after publication. Authors should ensure that file formats remain accessible and that documentation is sufficient for future re use. If data are updated after publication, maintain version notes and update the data statement accordingly.
Embargoes and Controlled Access
Sensitive data can be shared responsibly with appropriate safeguards.
When datasets include identifiable information, use repositories that provide controlled access mechanisms. Authors should explain how qualified researchers can request access and what approvals are required. If an embargo is needed to protect ongoing analyses, state the expected release date.
For clinical datasets, describe consent limitations and any legal restrictions. If data cannot be shared, provide a clear explanation and summarize the evidence supporting the etiological conclusions.
Citing and Versioning Data
Proper citations enable reuse and credit for data creators.
Include a recommended citation for your dataset and note the version used in the manuscript. If you update datasets after publication, provide a version history and update the data statement with new accession numbers.
Data Reuse and Licensing
Clear reuse terms support transparency and collaboration.
When possible, choose a data license that allows reuse with attribution. If restrictions apply, describe them clearly so secondary users understand limitations. Clear licensing increases trust and reduces ambiguity for follow on research.
Data Types and Documentation
Clear documentation improves reuse of diagnostic datasets.
Provide data dictionaries, codebooks, and protocol notes that explain variable definitions and preprocessing. For sequencing or imaging datasets, include software versions, quality control steps, and file formats that support reuse.
When possible, use non proprietary formats to improve accessibility for future researchers.
Data Availability Examples
Clear statements improve transparency.
Example: "Sequencing data are available in Repository X under accession number ABC123." If access is restricted, state the reason and provide a contact pathway for qualified requests.
Link Data to Manuscripts
Strong links improve citation and reuse.
Reference dataset identifiers in the Methods and Data Availability sections so readers can locate supporting evidence quickly.
Share Data Responsibly
Transparent data archiving strengthens trust in etiological diagnosis research.
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