FAIR Data Principles Compliance
PRISM FAIR Data Policy
This document outlines how the prism project implements the FAIR (Findable, Accessible, Interoperable, Reusable) data principles for psychological research data management.
F - FINDABLE
Implemented
Rich Metadata: Hierarchical JSON schemas with comprehensive descriptive fields
Unique Identifiers: Schema versioning with persistent URLs (
$idfields)Standardized Naming: BIDS-inspired file naming conventions
Searchable Categories: Taxonomized content tags and classifications
Keywords Support: Metadata fields for enhanced discoverability
In Development
DOI Integration: Support for dataset DOIs in metadata fields
ORCID Support: Creator identification via ORCID IDs
Dublin Core Export: Standardized metadata harvesting format
DataCite Compliance: DOI registration-ready metadata
Planned
Psychology Ontologies: Integration with CogPO, NIFSTD terminologies
Multilingual Support: Metadata in multiple languages
Semantic Annotations: Linked data capabilities
Repository Indexing: Automatic submission to psychology databases
A - ACCESSIBLE
Implemented
Open Source: GNU Affero General Public License v3.0 (AGPL-3.0)
Standard Formats: JSON, TSV, CSV for broad tool compatibility
Clear Documentation: Comprehensive README and schema documentation
Multiple Export Formats: Support for various output formats
In Development
FAIR Export Module: Dublin Core and DataCite metadata export
Repository Integration: Direct connection to OSF, Zenodo, DataVerse
Access Control Framework: Role-based permissions system
Long-term Preservation: Format migration and integrity checking
Planned
Federated Search: Cross-institutional data discovery
Cloud Integration: AWS, Google Cloud, Azure connectors
Embargo Management: Time-delayed data release
GDPR Compliance: Privacy-preserving data sharing
I - INTEROPERABLE
Implemented
JSON Schema Standards: Industry-standard validation framework
BIDS Inspiration: Alignment with neuroimaging data standards
Semantic Versioning: Predictable schema evolution
Modular Design: Extensible architecture for new modalities
In Development
Full BIDS Compliance: Complete alignment where applicable
API Standards: REST/GraphQL endpoints for data access
Format Converters: Automatic format transformation utilities
Cross-platform Support: Windows, macOS, Linux compatibility
Planned
FHIR Integration: Healthcare data interoperability
OMOP CDM Support: Longitudinal health research compatibility
Ontology Mapping: Automated concept alignment
SPARQL Endpoints: Semantic web query capabilities
R - REUSABLE
Implemented
Clear Licensing: Explicit CC and proprietary license support
Version Control: Git-based development with semantic versioning
Comprehensive Documentation: Schema details, examples, best practices
Community Guidelines: Contribution and governance frameworks
In Development
Provenance Tracking: Data lineage and processing history
Usage Examples: Sample datasets and analysis workflows
Quality Metrics: Automated data quality assessment
Training Materials: Workshops and educational resources
Planned
Citation Standards: Automatic citation generation
Impact Tracking: Usage analytics and metrics
Community Feedback: User rating and review system
Best Practices Library: Curated examples and guidelines
Implementation Roadmap
Phase 1: Foundation
Schema versioning system
Basic FAIR metadata fields
Dublin Core export functionality
Documentation framework
Phase 2: Enhanced Findability
DOI integration and validation
ORCID creator identification
Repository connectors (OSF, Zenodo)
Psychology ontology integration
Phase 3: Full Interoperability
Complete BIDS compliance
REST API development
Format conversion utilities
Cross-platform deployment
Phase 4: Advanced Features
Federated search capabilities
AI-powered metadata enhancement
Real-time collaboration tools
Community governance platform