De Identified Clinical Datasets
May be archived when re identification risk is assessed and controlled through accepted de identification procedures.
Data Archiving Permissions
Data Archiving Policy for Thrombosis and Treatments
JTT supports responsible data archiving that increases reproducibility while protecting participant rights, confidentiality obligations, and regulatory boundaries. Authors are encouraged to share de identified data, analysis code, and supporting documentation when permissions allow. This policy explains what can be archived, what restrictions apply, and how to communicate access conditions clearly in data availability statements.
Rigorous - Review StandardsCanonical Metric
Fast - Publication ProcessCanonical Metric
Global - Research CommunityCanonical Metric
Open - Access PublicationCanonical Metric
Archivable Material Categories
Archiving suitability depends on participant risk profile, consent coverage, and legal or institutional constraints.
Analysis Code and Scripts
Statistical scripts and workflow files are encouraged for reproducibility and methodological audit support.
Data Dictionaries
Variable definitions and coding frameworks should accompany archived data to improve interpretability.
Protocol Documentation
Protocol versions, amendments, and operational manuals may be archived to support transparency.
Permissions, Limits, and Author Responsibility
Authors are responsible for verifying whether data sharing is compatible with consent language, ethics approvals, local regulations, and institutional policy. If open release is not possible, the manuscript must include a clear statement explaining restrictions and controlled access pathways.
Data containing direct or indirect identifiers requires additional caution. In many cases, restricted access repositories or mediated data request workflows are the appropriate route. JTT may request clarification if statements are ambiguous, incomplete, or inconsistent with methods and participant details.
Where industry or multicenter agreements apply, contractual sharing limits should be disclosed with concise nonconfidential wording.
Recommended Data Availability Statement Elements
- Repository name and persistent record link when archived publicly.
- Access conditions and any approval steps for restricted datasets.
- Reason for limits where full public sharing is not permitted.
- Description of what supporting material remains available.
- Contact point for controlled data requests where relevant.
Strong data statements increase reviewer confidence and reduce late stage clarification requests.
Repository Selection and Quality Workflow
Select repositories with stable governance, persistent identifiers, and clear access controls aligned with health data sensitivity.
Assess Data Risk
Map privacy sensitivity and confirm what can be shared under consent and regulatory conditions.
Prepare Documentation
Create dictionaries, code explanations, and processing notes required for secondary interpretation.
Choose Repository
Select a repository model suitable for clinical data governance and long term access stability.
Publish Statement
Include precise data availability language in manuscript and metadata records.
Policy boundary: archiving permissions never override legal obligations, ethics constraints, or participant confidentiality protections.
Sensitive Dataset Governance in Clinical Context
Thrombosis studies often include high risk clinical variables and longitudinal care records. Data sharing should therefore follow a documented governance model that balances transparency with confidentiality obligations.
Minimum Necessary Disclosure
Share only variables required to validate core findings and remove fields that do not add reproducibility value.
Controlled Access Design
Where open release is not feasible, define request criteria, oversight body, and expected approval timeline.
Versioned Documentation
Record dataset versions and transformation history so secondary analysts can interpret context correctly.
Consent Alignment Check
Confirm that data sharing language remains fully aligned with participant consent and institutional approvals.
Clear governance notes in manuscript and repository records improve both trust and technical reuse quality.
Data Archive Quality Assurance
Archive records should include clear provenance, transformation logic, and access governance details. High quality data archiving is not only about storage location; it is about interpretability and safe reuse across future clinical research contexts.
Consistent archive documentation improves reproducibility and reduces misinterpretation risk.
Archive records should include context notes so secondary users can interpret variables without guessing source intent.
Archive Interpretability Standard
Data reuse quality depends on context clarity. Include collection conditions, transformation notes, and variable interpretation guidance so secondary users can evaluate findings accurately without reconstructing assumptions. Clear context supports reproducibility and protects against misclassification in future analysis.
Include archive update notes when dataset versions change after publication.
Quality Continuity Note
Consistent process quality depends on clear ownership, timely communication, and concise documentation of key actions. Applying these habits at every stage improves predictability, reduces avoidable delay, and strengthens confidence in both editorial and operational outcomes.
Need Data Sharing Clarification Before Submission?
Contact the editorial office early if your study includes restricted or sensitive thrombosis data so archiving language can be aligned in advance.
