Open Research Methodology

Theoretical Foundations

Transparent and rigorous methodology for academic research with BlueSky data, following international Open Science standards and FAIR principles.

Open ScienceFAIR DataGDPR CompliantReproducible

Our methodology is based on the principles of digital ethnography and social network analysis, specifically adapted for BlueSky's decentralized ecosystem.

Ethics

Ethical Principles

Rigorous compliance with privacy regulations and research ethics, ensuring user data protection.

GDPR compliance and privacy regulations
Only accessible public data
Automatic anonymization of sensitive data
Total transparency in methods and limitations

FAIR Data Standards

We rigorously follow the FAIR principles (Findable, Accessible, Interoperable, Reusable) to ensure maximum quality and reusability of research data.

Findable

Findable

Data is easily discoverable through rich metadata and persistent identifiers.

Persistent DOI for each dataset
Rich metadata in Dublin Core format
Indexing in academic repositories
Structured keywords for discovery
Accessible

Accessible

Programmatic access and multiple formats, following standard protocols and complete documentation.

Public REST API for programmatic access
Multiple export formats
Complete access documentation
Standard protocols (HTTP, JSON, CSV)
Interoperable

Interoperable

Compatibility with standard analysis tools and structured formats with controlled vocabularies.

Standard formats (JSON-LD, CSV, RDF)
Controlled vocabularies and ontologies
SPSS, R, Python, NVivo compatibility
Standardized metadata schemas
Reusable

Reusable

Reusable data with clear licenses, complete documentation, and open code.

Clear licenses (CC BY 4.0)
Complete data provenance
Detailed methodological documentation
Open processing code