Responsible Data Sharing for Neuroscience Research
JNPP supports ethical data archiving to improve transparency, reproducibility, and long term research value. This page explains how to share data responsibly while protecting participant privacy and institutional requirements. Early planning helps align with funder and institutional policies.
Why Data Archiving Matters
Neuroscience advances faster when data are discoverable and reusable. Archiving ensures that methods can be verified, results can be replicated, and new analyses can build on previous work. JNPP supports FAIR aligned practices for findability and reuse.
Transparency and Reproducibility
Archiving enables reviewers and readers to understand how results were generated. Clear datasets and code improve trust in findings, especially in complex neurophysiology and imaging studies.
Participant Privacy and Ethics
Data sharing must follow consent agreements, institutional policies, and applicable regulations. Use de identification, access controls, or restricted repositories when necessary to protect sensitive participant information.
Long Term Research Value
Archived data support secondary analysis, meta research, and method development. When possible, deposit data in recognized repositories with persistent identifiers to ensure lasting access.
What to Archive and How to Prepare It
Archive the materials that are essential to understanding and reproducing the research. The level of detail should match the complexity of the study.
Imaging and Electrophysiology Data
For imaging, include raw or preprocessed files, acquisition parameters, and preprocessing details. For electrophysiology, provide sampling rates, filtering methods, and event definitions. Clear metadata enables reliable interpretation and reuse.
Behavioral and Clinical Datasets
Provide de identified behavioral data, clinical outcomes, and assessment instruments. Include code books, scoring rules, and time point definitions so secondary users can interpret the dataset correctly and avoid misclassification.
Code, Scripts, and Analysis Pipelines
Share analysis scripts, software versions, and parameter settings. Well organized code supports reproducibility and allows reviewers to validate findings. If code cannot be shared, explain why and provide sufficient methodological detail.
Data Sharing Expectations
JNPP requires a data availability statement for every submission. The statement should describe where data are stored and how access is granted. Provide repository links at submission when possible. This avoids delays during production. Editors may request clarification when needed before acceptance.
Select an Appropriate Repository
Use domain specific or institutional repositories whenever possible. Choose platforms that provide stable identifiers, clear access terms, and long term preservation for neuroscience datasets and code.
Prepare Data and Documentation
Provide README files, variable definitions, and clear methodology notes. Well documented data improve reuse and reduce misinterpretation in secondary analysis.
Describe Access and Restrictions
If data are restricted due to privacy, intellectual property, or clinical regulations, describe the access pathway and governance process. Editors will review restrictions for compliance.
Update Statements After Revision
If data locations or access terms change during revision, update your data availability statement before final acceptance. Accurate statements reduce publication delays and help readers locate resources quickly.
Data Archiving FAQ
These answers clarify what is expected for neuroscience data sharing.
Is data sharing mandatory?
Can I provide controlled access?
What if my institution restricts data sharing?
Do I need to share raw data or processed data?
Are embargo periods allowed?
Strengthen Reproducibility and Trust
Responsible data archiving increases confidence in neuroscience findings and improves long term research impact. Clear archiving improves citations and collaboration opportunities. Contact the editorial office if you need guidance on data sharing options.
