Data Archiving Permissions

Clear guidance on data sharing for neurological research and therapy.

JNRT supports responsible data sharing to improve reproducibility and enable secondary analysis in neurological research. Authors should deposit datasets in recognized repositories and include clear data availability statements.

Transparent data practices strengthen trust, accelerate discovery, and support evidence based therapy development.

• Neuroimaging: OpenNeuro, NeuroVault
• Genomics: NCBI GEO, SRA, ENA
• Clinical data: institutional or controlled access repositories
• General repositories: Zenodo, Figshare, Dryad

Select repositories that match the data type, provide stable identifiers, and allow long term access. Institutional repositories may be used when specialized repositories are not available.

Provide a short readme file that explains file structure, variable definitions, and software requirements. Clear documentation reduces reuse friction and supports verification.

• Name files consistently and include version numbers
• Describe data cleaning or transformation steps
• Link protocols or code repositories when available

Provide the data required for independent verification of results, including raw data, processed outputs, and metadata describing sample preparation and study design.

• Raw imaging or sequencing files when possible
• Processed datasets used for analysis
• Metadata for participants, cohorts, or models
• Quality control summaries and thresholds

Include a data availability statement describing where data are stored, how to access them, and any restrictions. Provide accession numbers or DOIs whenever possible.

If data are under embargo or controlled access, explain the reason and describe the access pathway for qualified researchers.

Use standard file formats to improve interoperability and reuse. Provide clear metadata for sample preparation, imaging protocols, and analysis pipelines.

Well structured metadata reduces misinterpretation and supports reanalysis by independent groups.

Analytical code and workflows improve reproducibility. Share scripts, pipelines, and software versions when feasible. If code cannot be shared, provide detailed methods for independent verification.

Imaging studies should report acquisition parameters, preprocessing steps, and analysis pipelines. Provide clear descriptions of regions of interest, segmentation methods, and statistical thresholds.

Provide reference genome versions, alignment tools, and filtering criteria for genomic analyses. Include accession numbers for sequence data and document normalization methods.

For patient level or sensitive datasets, follow privacy regulations and ethics approvals. De identify data and use controlled access systems when required.

JNRT supports responsible sharing that balances openness with participant protection.

Embargoes may be granted when justified by regulatory or intellectual property requirements. Authors should state the embargo end date and provide an access pathway for qualified researchers.

Digital preservation supported through distributed archiving and regular backups. This ensures long term access to published data and supporting materials.

Cite datasets in the reference list and include DOIs or accession numbers. Clear citation supports credit for data generation and helps readers locate supporting evidence.

Consistent data citation improves transparency and supports reproducibility across studies.

Plan data sharing early in the research workflow so that repositories, metadata, and access permissions are ready at submission.

• Select an appropriate repository for the data type
• Prepare metadata and documentation for reuse
• Deposit raw and processed files with accession numbers
• Link datasets in the manuscript and data statement

JNRT encourages responsible reuse of datasets with appropriate attribution. If you reuse public data, cite the original dataset and describe how it was integrated into the analysis.

Clear reuse documentation improves trust and supports secondary analysis by other teams.

Transparent reuse statements help reviewers assess data provenance and integrity.

• Clear documentation of methods and protocols
• Accession numbers or DOIs included
• Metadata describes sample and cohort details
• Data files are complete and readable
• Access instructions are clearly stated

• Data deposition is strongly encouraged for reproducibility
• Controlled access may be used for sensitive data
• Provide repository links and accession numbers
• Clear metadata improves reuse and validation