Data Sharing Plan AI Prompt

Help me create a data sharing plan that maximizes openness while addressing legal, ethical, and practical constraints.

Data type: {{data_type}}
Participant population: {{population}}
Funder requirements: {{funder}} (e.g. NIH, NSF, Wellcome Trust, EU Horizon)
Journal requirements: {{journal}}

1. Determine the appropriate level of data sharing:

   Fully open (preferred when possible):
   - Data deposited in a public repository with no access controls
   - Appropriate when: data contains no identifying information and poses no re-identification risk
   - Repositories: OSF, Zenodo, Figshare, domain-specific repositories (ICPSR, UKDA, GenBank, etc.)

   Restricted access:
   - Data available to qualified researchers upon request or through an application process
   - Appropriate when: data contains sensitive information but de-identification is not sufficient
   - Repositories: UKDA, ICSPR Restricted Access, institutional data repository

   Available on request:
   - Data available by contacting the authors
   - Least preferred: frequently data becomes unavailable after author changes institution
   - Appropriate only when: repository deposit is genuinely not possible

   Not shared:
   - Appropriate only when: legal or ethical prohibitions exist (classified data, legally protected patient records)
   - Must provide a clear statement of why data cannot be shared

2. De-identification requirements:
   - Apply Safe Harbor method (HIPAA): remove the 18 specified identifiers
   - Apply Expert Determination: a qualified expert certifies re-identification risk is very small
   - For small or unusual populations: even 'de-identified' data may be re-identifiable — consider restricted access
   - Synthetic data: generate synthetic data that preserves statistical properties without individual records

3. Metadata and documentation:
   - Data without documentation is nearly unusable
   - Provide: a codebook for every variable (name, label, values, missing codes), a data collection instrument, and a processing log describing all transformations from raw to analysis-ready data

4. Consent language (for future studies):
   - Consent forms should include explicit language about data sharing
   - Recommended language: 'De-identified data from this study may be shared with other researchers via a secure repository to enable verification of results and future research.'

5. Funder-specific requirements:
   - NIH: Data Management and Sharing Plan required for all funded studies
   - NSF: similar requirements, check program-specific guidance
   - EU Horizon: 'open by default' requirement with possibility of exceptions
   Write the data management plan text appropriate for {{funder}}.

Return: data sharing recommendation, de-identification procedure, repository selection, metadata checklist, and data management plan text for the funder.