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Product Backlog & Feature Roadmap

This page tracks planned features, enhancements, and research directions for Open Navigator. Items are organized by theme and priority.

🎯 High Priority Features​

Politician Personality Profiles​

Status: Planned
Reference: Personality Politics - Joe Biden Example

Create comprehensive personality and behavioral profiles for elected officials based on:

  • Public Voting Records: Analyze voting patterns, bill sponsorships, and legislative priorities
  • Public Statements: Analyze speeches, press releases, social media, and meeting transcripts
  • Psychological Frameworks: Apply Big Five personality traits, moral foundations, leadership styles
  • Communication Patterns: Analyze rhetoric, framing strategies, and messaging consistency
  • Constituency Alignment: Compare positions with constituent demographics and values

Data Sources:

  • OpenStates API (voting records, bill sponsorships)
  • Meeting transcripts from events_text_ai (local positions and rhetoric)
  • Social media APIs (public statements)
  • Campaign finance data (FEC API)
  • Census data (constituency demographics)

Output Format:

{
  "person_id": "ocd-person/12345",
  "full_name": "Jane Smith",
  "office": "City Council Member, District 3",
  "jurisdiction": "Boston, MA",
  "personality_profile": {
    "big_five": {
      "openness": 0.75,
      "conscientiousness": 0.82,
      "extraversion": 0.68,
      "agreeableness": 0.71,
      "neuroticism": 0.35
    },
    "moral_foundations": {
      "care_harm": 0.85,
      "fairness_cheating": 0.78,
      "loyalty_betrayal": 0.52,
      "authority_subversion": 0.48,
      "sanctity_degradation": 0.42,
      "liberty_oppression": 0.71
    },
    "leadership_style": "collaborative",
    "policy_priorities": ["housing", "education", "climate"],
    "communication_style": {
      "clarity_score": 0.82,
      "consistency_score": 0.76,
      "emotional_tone": "optimistic"
    }
  },
  "voting_analysis": {
    "total_votes": 247,
    "attendance_rate": 0.94,
    "party_loyalty_score": 0.68,
    "bipartisan_collaboration_score": 0.45,
    "key_issues": [
      {
        "issue": "affordable_housing",
        "vote_count": 32,
        "support_rate": 0.91,
        "alignment_with_platform": 0.95
      }
    ]
  },
  "constituent_alignment": {
    "demographic_match": 0.72,
    "policy_position_match": 0.68,
    "responsiveness_score": 0.81
  },
  "sources": [
    "OpenStates voting records",
    "City Council meeting transcripts",
    "Campaign website positions",
    "Social media analysis (Twitter/X, Facebook)"
  ],
  "last_updated": "2026-05-05"
}

Implementation Steps:

  1. ✅ Create bronze_contacts table (DONE - already exists)
  2. ✅ Extract people from meeting transcripts (DONE)
  3. 🔲 Build personality analysis pipeline using LLMs
  4. 🔲 Integrate voting record analysis from OpenStates
  5. 🔲 Apply psychological frameworks (Big Five, Moral Foundations)
  6. 🔲 Create profile aggregation and scoring system
  7. 🔲 Build UI components for profile visualization
  8. 🔲 Add profile comparison tools (compare candidates, track changes over time)

Related Tables:

  • bronze_contacts - People extracted from meetings
  • opencivicdata_person - Legislators from OpenStates
  • bronze_decisions - Voting behavior in local meetings
  • bronze_organizations - Organizational affiliations

📊 Data & Analytics Features​

Multi-Model AI Evaluation Dashboard​

Status: In Progress (documentation complete, implementation pending)

Visual dashboard to compare AI model extractions and show consensus/contradictions.

Features:

  • Side-by-side comparison of model outputs
  • Consensus visualization (what all models agree on)
  • Contradiction highlighting with explanation
  • Quality metrics (Faithfulness, Relevancy, Coherence)
  • Model performance tracking over time

Reference: AI Model Evaluation

Advanced Frame Analysis Aggregation​

Status: Planned

Build aggregated views of policy frame analysis across:

  • Time (how frames evolve)
  • Geography (regional differences in framing)
  • Issues (dominant frames per topic)
  • Decision outcomes (which frames predict success/failure)

Predictive Analytics​

Status: Research Phase

Use historical meeting data to predict:

  • Likely decision outcomes based on arguments presented
  • Budget allocation patterns
  • Policy adoption timelines
  • Public engagement levels

🔍 Search & Discovery​

Semantic Search Across All Content​

Status: Partially Implemented

Expand semantic search to cover:

  • Meeting transcripts
  • Decision statements
  • Nonprofit descriptions
  • Elected official statements
  • Legislation text

Advanced Filtering​

Status: Planned

Multi-dimensional filtering:

  • Geographic (state → county → city → district)
  • Temporal (date ranges, meeting frequency)
  • Thematic (COFOG codes, NTEE categories)
  • Sentiment (supportive vs. opposed arguments)
  • Financial impact (budget thresholds)

🤝 Collaboration & Engagement​

Constituent Communication Tools​

Status: Planned

Help residents engage with elected officials:

  • Template generator for public comments
  • Meeting reminder notifications
  • Issue tracking (follow specific topics)
  • Elected official contact finder
  • Public comment submission tracking

Advocacy Campaign Builder​

Status: Planned

Tools for organizers:

  • Campaign strategy templates
  • Target identification (key decision-makers)
  • Power mapping visualization
  • Coalition building tools
  • Impact measurement dashboard

🧠 AI & Machine Learning​

Fine-Tuned Models for Civic Analysis​

Status: Research Phase

Train domain-specific models:

  • Civic-BERT: Fine-tuned for government meeting analysis
  • Policy-Frame-GPT: Specialized in frame analysis
  • Vote-Predictor: Predict council vote outcomes
  • Sentiment-Civic: Sentiment analysis for public comments

Ensemble Model Implementation​

Status: In Progress

Implement production-ready ensemble pipelines:

  • Automated MoA synthesis for all new meetings
  • Multi-model comparison for quality assurance
  • Confidence scoring for extracted facts
  • Human-in-the-loop for low-confidence items

Reference: AI Model Merging

🗺️ Geographic & Spatial Features​

Interactive Power Maps​

Status: Planned

Visualize power dynamics from frame analysis:

  • Stakeholder influence networks
  • Constituent vs. developer interests
  • Coalition formation patterns
  • Decision-making pathways

Geospatial Analysis​

Status: Planned

Map-based views:

  • Jurisdictions by policy topic heatmap
  • Nonprofit density by issue area
  • Meeting frequency by region
  • Budget allocation patterns

📱 Platform & Infrastructure​

Mobile Application​

Status: Planned

Native mobile apps for:

  • Meeting notifications
  • Live meeting viewing with AI summaries
  • Quick contact lookup for elected officials
  • Voice-to-text public comment submission

Real-Time Meeting Analysis​

Status: Research Phase

Live AI analysis during meetings:

  • Real-time transcription and analysis
  • Live frame detection
  • Decision outcome prediction
  • Instant fact-checking of claims

Multi-Language Support​

Status: Planned

Expand to support:

  • Spanish (priority)
  • Chinese
  • Vietnamese
  • Tagalog
  • Other languages based on jurisdiction demographics

🔒 Privacy & Security​

Differential Privacy Implementation​

Status: Research Phase

Protect individual privacy while enabling analysis:

  • Anonymized voting patterns
  • Aggregated demographic analysis
  • Privacy-preserving personality profiles

Data Governance Framework​

Status: Planned

Implement comprehensive governance:

  • Data retention policies
  • Right to be forgotten mechanisms
  • Consent management system
  • Audit logging for all data access

🧪 Research & Experiments​

Causal Analysis of Policy Outcomes​

Status: Research Phase

Use causal inference to understand:

  • What policy interventions actually work
  • Impact of framing on decision outcomes
  • Effect of constituent engagement on votes
  • Budget allocation effectiveness

Comparative Jurisdiction Analysis​

Status: Planned

Compare similar jurisdictions:

  • Best practices identification
  • Policy diffusion patterns
  • Regional coordination opportunities
  • Performance benchmarking

LLM-Generated Policy Briefs​

Status: Planned

Automatically generate:

  • Meeting summaries for residents
  • Policy impact analyses
  • Comparison reports ("What did other cities do?")
  • FAQ generation from meeting transcripts

🎨 User Experience​

Personalized Dashboard​

Status: Planned

Customizable views based on user interests:

  • "My Neighborhood" - local-only updates
  • "My Issues" - filtered by policy topics
  • "My Representatives" - track specific officials
  • "My Meetings" - saved/bookmarked meetings

Accessibility Improvements​

Status: Ongoing

Enhance accessibility:

  • Screen reader optimization
  • Keyboard navigation
  • High contrast themes
  • Simplified language mode
  • Audio descriptions for visualizations

📚 Documentation & Education​

Civic Education Curriculum​

Status: Planned

Educational materials:

  • "How Government Works" guides
  • "Understanding Your Local Budget" tutorials
  • "How to Make Public Comments" videos
  • "Reading Meeting Minutes" guides

API Documentation​

Status: Partially Complete

Comprehensive developer docs:

  • REST API reference
  • GraphQL schema
  • Authentication guides
  • Rate limiting policies
  • Code examples in multiple languages

🔗 Integration Goals​

Third-Party Integrations​

Status: Planned

Connect with:

  • Civic platforms: Participatory budgeting tools, petition platforms
  • Social media: Auto-post meeting summaries
  • Calendar apps: Meeting reminders
  • Communication tools: Slack, Discord for community organizing
  • CRM systems: For advocacy organizations

Data Export & Portability​

Status: Planned

Enable data export:

  • CSV/Excel for offline analysis
  • JSON API for programmatic access
  • PDF reports for sharing
  • Parquet files for data science
  • Push to HuggingFace Datasets

💡 Community Requested Features​

Issue Tracking​

Status: Planned

Track specific issues across time:

  • "Follow this bill through the legislative process"
  • "Alert me when budget item is discussed"
  • "Track mentions of my neighborhood"

Comparison Tools​

Status: Planned

Compare across dimensions:

  • Before/after policy implementation
  • Your city vs. neighboring cities
  • Current council vs. previous council
  • Campaign promises vs. actual votes

Public Comment Analysis​

Status: Planned

Analyze public comments:

  • Common themes in constituent feedback
  • Sentiment trends over time
  • Impact of public comment on votes
  • Who speaks at meetings (demographics)

📅 Timeline (Rough Estimates)​

Q2 2026​

  • ✅ Multi-model comparison infrastructure (COMPLETE)
  • ✅ MoA synthesis pipeline (COMPLETE)
  • 🔲 Politician personality profiles (v1 prototype)
  • 🔲 Multi-model evaluation dashboard

Q3 2026​

  • 🔲 Fine-tuned civic models
  • 🔲 Advanced filtering
  • 🔲 Mobile app (beta)
  • 🔲 Real-time meeting analysis (pilot)

Q4 2026​

  • 🔲 Interactive power maps
  • 🔲 Multi-language support (Spanish)
  • 🔲 Constituent communication tools
  • 🔲 API v2 launch

2027+​

  • 🔲 Predictive analytics
  • 🔲 Causal analysis research
  • 🔲 Civic education curriculum
  • 🔲 Global expansion

🤝 How to Contribute​

Have ideas for new features? Want to help implement something from this backlog?

  1. Comment on existing issues: GitHub Issues
  2. Submit feature requests: Use the "Feature Request" template
  3. Join discussions: GitHub Discussions
  4. Pick a backlog item: Comment on the issue to claim it
  5. Submit a PR: Reference the backlog item in your pull request

📊 Priority Framework​

We prioritize features using:

Impact: How many users benefit? (🔴 High / 🟡 Medium / 🟢 Low)
Effort: How much work is required? (🟢 Low / 🟡 Medium / 🔴 High)
Strategic: Does it align with our mission? (⭐ Yes / - No)

High Priority: 🔴 Impact + 🟢 Low Effort + ⭐ Strategic
Medium Priority: 🟡 Impact + 🟡 Effort + ⭐ Strategic
Research Phase: 🔴 Impact + 🔴 High Effort (needs more investigation)

🎯 Feature Status Legend​

  • ✅ Complete - Feature is live and available
  • 🔄 In Progress - Actively being developed
  • 🔲 Planned - Committed to roadmap
  • 🧪 Research Phase - Exploring feasibility
  • 💭 Idea - Community suggestion, not yet scoped

Last updated: May 5, 2026
Next review: June 1, 2026