Evidence-Based Funding

Every funding decision backed by transparent, verifiable data. Our multi-dimensional metrics framework ensures resources reach the tools researchers actually depend on.

Note: This is only an exemplar draft to demonstrate the concept. There are several details (such as the ceiling and floor for the metrics) that are not defined and should be determined.

📊 Comprehensive Metrics Framework

🎯 Usage Metrics (40% weight)

📈 Download & Installation Tracking

  • Package manager downloads (PyPI, CRAN, npm, etc.)
  • Docker image pulls and container usage
  • Source code downloads and repository clones
  • GitHub Stars and Forks
  • Binary distribution downloads

👥 Active User Measurement

  • Unique user identification (privacy-preserving)
  • Session duration and frequency analysis
  • Feature utilization patterns
  • Geographic distribution of users

🔗 Dependency Network Analysis

  • Software packages that depend on the tool
  • Critical infrastructure dependencies
  • Ecosystem integration depth
  • Interoperability contributions

🎓 Academic Impact (30% weight)

📝 Publication Citations

  • Direct citations in peer-reviewed literature
  • Acknowledgments in methods sections
  • Software-specific citation tracking
  • Impact factor weighting of citing journals

💰 Grant Proposal Mentions

  • Funding applications citing the software
  • Total funding volume associated with usage
  • Success rate of proposals using the tools
  • International funding agency recognition

🔬 Research Output Attribution

  • Datasets generated using the software
  • Reproducibility studies and replications
  • Meta-analyses incorporating tool-derived results
  • Policy documents citing research enabled by tools

🤝 Community Health (20% weight)

👨‍💻 Contributor Activity

  • Number of active contributors
  • Diversity of contributor institutions
  • Code contribution frequency and quality
  • Mentorship and onboarding success

📚 Documentation Quality

  • Documentation completeness assessments
  • User experience testing results
  • Tutorial effectiveness measurements
  • Accessibility compliance scores

💬 Support Responsiveness

  • Issue resolution time and quality
  • Community forum engagement levels
  • User satisfaction survey results
  • Knowledge sharing and collaboration metrics

🚀 Innovation Potential (10% weight)

🔧 Technical Advancement

  • Novel algorithm implementations
  • Performance improvements and optimizations
  • Security enhancements and best practices
  • Scalability and efficiency gains

🌐 Cross-Domain Impact

  • Adoption across different research fields
  • Interdisciplinary collaboration facilitation
  • Standard-setting contributions
  • Educational and training applications

🔍 Data Collection & Privacy

Privacy-First Approach

🔒 Data Minimization

We collect only the data necessary for funding allocation decisions, using aggregated and anonymized metrics wherever possible.

🛡️ User Consent

All user-level data collection requires explicit consent with clear opt-out mechanisms and data deletion rights.

🔐 Secure Storage

All metrics data is encrypted at rest and in transit, with access limited to authorized personnel only.

Automated Collection Methods

📊 Package Manager APIs

Automated collection from PyPI, CRAN, npm, and other package repositories

🔍 Academic Database Crawling

Regular scanning of PubMed, arXiv, Google Scholar for citations and mentions

📈 Repository Analytics

GitHub, GitLab, and other repository platform metrics integration

🤖 Self-Reporting Tools

Optional lightweight telemetry for projects that choose to participate

📈 Real-Time Dashboard

Public Transparency Portal

Our commitment to transparency includes a public dashboard showing:

💰 Funding Allocation

Real-time view of funding distribution across projects and categories

📊 Impact Metrics

Live updates of usage statistics, citations, and community health indicators

🎯 Performance Tracking

Progress indicators for funded projects and ecosystem health metrics

🔍 Audit Trail

Complete history of funding decisions with supporting rationale

Interactive Features

  • Custom Queries: Stakeholders can create custom views and reports
  • Export Capabilities: Data available in multiple formats for analysis
  • Historical Trends: Long-term trends and pattern analysis
  • Comparative Analysis: Cross-project and cross-domain comparisons

🎯 Impact Assessment

Success Indicators

🔧 Tool Reliability

  • Reduced bug reports and security vulnerabilities
  • Improved software stability and performance
  • Faster issue resolution times
  • Enhanced user satisfaction scores

🎓 Research Productivity

  • Increased publication rates using supported tools
  • Reduced time spent on technical troubleshooting
  • Greater reproducibility of research results
  • Enhanced collaboration across institutions

💼 Career Sustainability

  • Stable employment for research software engineers
  • Professional development and career advancement
  • Recognition for maintenance contributions
  • Reduced burnout and turnover rates

🌍 Ecosystem Health

  • Increased diversity in contributor base
  • Improved documentation and user onboarding
  • Greater interoperability between tools
  • Stronger international collaboration