Changes for page Requirements

Last modified by Robert Schaub on 2025/12/23 11:03

From 2.1 to 1.1 From 7.1 to 6.1

From version 6.1

edited by Robert Schaub
on 2025/12/23 08:03

Change comment: Imported from XAR

To version 2.1

edited by Robert Schaub
on 2025/12/22 19:46

Change comment: Imported from XAR

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@@ -306,7 +306,7 @@
 . How common is this pattern?
 . Store in ErrorPattern table (improvement queue)
--=== 6.2 Continuous Improvement Cycle ===
++=== 6.2 Weekly Improvement Cycle ===
 . **Review**: Analyze top error patterns
 . **Develop**: Create fix (prompt, model, validation)
@@ -326,7 +326,7 @@
  * Re-work rate
  * Claims processed per hour
--**Goal**: continuous improvement in error rate
++**Goal**: 10% monthly improvement in error rate
  == 7. Automated Quality Monitoring ==
@@ -803,405 +803,185 @@
  === NFR12: Security Controls ===
--**Fulfills:** Data protection, system integrity, user privacy, production readiness
++**Fulfills:** Production readiness, legal compliance
--**Phase:** Beta 0 (essential), V1.0 (complete) **BLOCKER**
++**Requirements:**
++1. **Input Validation:** SQL injection, XSS, CSRF prevention
++2. **Rate Limiting:** 5 analyses per minute per IP
++3. **Authentication:** Secure sessions, API key rotation
++4. **Data Protection:** HTTPS, encryption, backups
++5. **Security Audit:** Penetration testing, GDPR compliance
--**Purpose:** Protect FactHarbor systems, user data, and operations from security threats, ensuring production-grade security posture.
++**Milestone:** Beta 0 (essential), V1.0 (complete) **BLOCKER**
--**Specification:**
--
--==== API Security ====
--
--**Rate Limiting:**
--* **Analysis endpoints:** 100 requests/hour per IP
--* **Read endpoints:** 1,000 requests/hour per IP
--* **Search:** 500 requests/hour per IP
--* **Authenticated users:** 5x higher limits
--* **Burst protection:** Max 10 requests/second
--
--**Authentication & Authorization:**
--* **API Keys:** Required for programmatic access
--* **JWT tokens:** For user sessions (1-hour expiry)
--* **OAuth2:** For third-party integrations
--* **Role-Based Access Control (RBAC):**
--  * Public: Read-only access to published claims
--  * Contributor: Submit claims, provide evidence
--  * Moderator: Review contributions, manage quality
--  * Admin: System configuration, user management
--
--**CORS Policies:**
--* Whitelist approved domains only
--* No wildcard origins in production
--* Credentials required for sensitive endpoints
--
--**Input Sanitization:**
--* Validate all user input against schemas
--* Sanitize HTML/JavaScript in text submissions
--* Prevent SQL injection (use parameterized queries)
--* Prevent command injection (no shell execution of user input)
--* Max request size: 10MB
--* File upload restrictions: Whitelist file types, scan for malware
--
-----
--
--==== Data Security ====
--
--**Encryption at Rest:**
--* Database encryption using AES-256
--* Encrypted backups
--* Key management via cloud provider KMS (AWS KMS, Google Cloud KMS)
--* Regular key rotation (90-day cycle)
--
--**Encryption in Transit:**
--* HTTPS/TLS 1.3 only (no TLS 1.0/1.1)
--* Strong cipher suites only
--* HSTS (HTTP Strict Transport Security) enabled
--* Certificate pinning for mobile apps
--
--**Secure Credential Storage:**
--* Passwords hashed with bcrypt (cost factor 12+)
--* API keys encrypted in database
--* Secrets stored in environment variables (never in code)
--* Use secrets manager (AWS Secrets Manager, HashiCorp Vault)
--
--**Data Privacy:**
--* Minimal data collection (privacy by design)
--* User data deletion on request (GDPR compliance)
--* PII encryption in database
--* Anonymize logs (no PII in log files)
--
-----
--
--==== Application Security ====
--
--**OWASP Top 10 Compliance:**
--
--1. **Broken Access Control:** RBAC implementation, path traversal prevention
--2. **Cryptographic Failures:** Strong encryption, secure key management
--3. **Injection:** Parameterized queries, input validation
--4. **Insecure Design:** Security review of all features
--5. **Security Misconfiguration:** Hardened defaults, security headers
--6. **Vulnerable Components:** Dependency scanning (see below)
--7. **Authentication Failures:** Strong password policy, MFA support
--8. **Data Integrity Failures:** Signature verification, checksums
--9. **Security Logging Failures:** Comprehensive audit logs
--10. **Server-Side Request Forgery:** URL validation, whitelist domains
--
--**Security Headers:**
--* `Content-Security-Policy`: Strict CSP to prevent XSS
--* `X-Frame-Options`: DENY (prevent clickjacking)
--* `X-Content-Type-Options`: nosniff
--* `Referrer-Policy`: strict-origin-when-cross-origin
--* `Permissions-Policy`: Restrict browser features
--
--**Dependency Vulnerability Scanning:**
--* **Tools:** Snyk, Dependabot, npm audit, pip-audit
--* **Frequency:** Daily automated scans
--* **Action:** Patch critical vulnerabilities within 24 hours
--* **Policy:** No known high/critical CVEs in production
--
--**Security Audits:**
--* **Internal:** Quarterly security reviews
--* **External:** Annual penetration testing by certified firm
--* **Bug Bounty:** Public bug bounty program (V1.1+)
--* **Compliance:** SOC 2 Type II certification target (V1.5)
--
-----
--
--==== Operational Security ====
--
--**DDoS Protection:**
--* CloudFlare or AWS Shield
--* Rate limiting at CDN layer
--* Automatic IP blocking for abuse patterns
--
--**Monitoring & Alerting:**
--* Real-time security event monitoring
--* Alerts for:
--  * Failed login attempts (>5 in 10 minutes)
--  * API abuse patterns
--  * Unusual data access patterns
--  * Security scan detections
--* Integration with SIEM (Security Information and Event Management)
--
--**Incident Response:**
--* Documented incident response plan
--* Security incident classification (P1-P4)
--* On-call rotation for security issues
--* Post-mortem for all security incidents
--* Public disclosure policy (coordinated disclosure)
--
--**Backup & Recovery:**
--* Daily encrypted backups
--* 30-day retention period
--* Tested recovery procedures (quarterly)
--* Disaster recovery plan (RTO: 4 hours, RPO: 1 hour)
--
-----
--
--==== Compliance & Standards ====
--
--**GDPR Compliance:**
--* User consent management
--* Right to access data
--* Right to deletion
--* Data portability
--* Privacy policy published
--
--**Accessibility:**
--* WCAG 2.1 AA compliance
--* Screen reader compatibility
--* Keyboard navigation
--* Alt text for images
--
--**Browser Support:**
--* Modern browsers only (Chrome/Edge/Firefox/Safari latest 2 versions)
--* No IE11 support
--
--**Acceptance Criteria:**
--
--* ✅ Passes OWASP ZAP security scan (no high/critical findings)
--* ✅ All dependencies with known vulnerabilities patched
--* ✅ Penetration test completed with no critical findings
--* ✅ Rate limiting blocks abuse attempts
--* ✅ Encryption at rest and in transit verified
--* ✅ Security headers scored A+ on securityheaders.com
--* ✅ Incident response plan documented and tested
--* ✅ 95% uptime over 30-day period
--
--
  === NFR13: Quality Metrics Transparency ===
--**Fulfills:** User trust, transparency, continuous improvement, IFCN methodology transparency
++**Fulfills:** IFCN transparency, user trust
--**Phase:** POC2 (internal), Beta 0 (public), V1.0 (real-time)
++**Public Metrics:**
++* Quality gates performance
++* Evidence quality stats
++* Hallucination rate
++* User feedback
--**Purpose:** Provide transparent, measurable quality metrics that demonstrate AKEL's performance and build user trust in automated fact-checking.
++**Milestone:** POC2 (internal), Beta 0 (public), V1.0 (real-time)
--**Specification:**
++== 10. Requirements Priority Matrix ==
--==== Component: Public Quality Dashboard ====
++This table shows all functional and non-functional requirements ordered by urgency and priority.
--**Core Metrics to Display:**
++**Note:** Implementation phases (POC1, POC2, Beta 0, V1.0) are defined in [[POC Requirements>>FactHarbor.Specification.POC.Requirements]] and [[Implementation Roadmap>>FactHarbor.Implementation-Roadmap.WebHome]], not in this priority matrix.
--**1. Verdict Quality Metrics**
++**Priority Levels:**
++* **CRITICAL** - System doesn't work without it, or major safety/legal risk
++* **HIGH** - Core functionality, essential for success
++* **MEDIUM** - Important but not blocking
++* **LOW** - Nice to have, can be deferred
--**TIGERScore (Fact-Checking Quality):**
--* **Definition:** Measures how well generated verdicts match expert fact-checker judgments
--* **Scale:** 0-100 (higher is better)
--* **Calculation:** Using TIGERScore framework (Truth-conditional accuracy, Informativeness, Generality, Evaluativeness, Relevance)
--* **Target:** Average ≥80 for production release
--* **Display:**
--{{code}}
--Verdict Quality (TIGERScore):
--Overall: 84.2 ▲ (+2.1 from last month)
++**Urgency Levels:**
++* **HIGH** - Immediate need (critical for proof of concept)
++* **MEDIUM** - Important but not immediate
++* **LOW** - Future enhancement
--Distribution:
--  Excellent (>80): 67%
--  Good (60-80): 28%
--  Needs Improvement (<60): 5%
++|= ID |= Title |= Priority |= Urgency
++| **HIGH URGENCY** |||
++| **FR1** | Claim Intake | CRITICAL | HIGH
++| **FR5** | Evidence Collection | CRITICAL | HIGH
++| **FR7** | Verdict Computation | CRITICAL | HIGH
++| **NFR11** | Quality Assurance Framework | CRITICAL | HIGH
++| **FR2** | Claim Normalization | HIGH | HIGH
++| **FR3** | Claim Classification | HIGH | HIGH
++| **FR4** | Scenario Generation | HIGH | HIGH
++| **FR6** | Evidence Evaluation | HIGH | HIGH
++| **MEDIUM URGENCY** |||
++| **NFR12** | Security Controls | CRITICAL | MEDIUM
++| **FR9** | Corrections | HIGH | MEDIUM
++| **FR44** | ClaimReview Schema | HIGH | MEDIUM
++| **FR45** | Corrections Notification | HIGH | MEDIUM
++| **FR48** | Safety Framework | HIGH | MEDIUM
++| **NFR3** | Transparency | HIGH | MEDIUM
++| **NFR13** | Quality Metrics | HIGH | MEDIUM
++| **FR8** | User Contribution | MEDIUM | MEDIUM
++| **FR10** | Publishing | MEDIUM | MEDIUM
++| **FR13** | API | MEDIUM | MEDIUM
++| **FR46** | Image Verification | MEDIUM | MEDIUM
++| **FR47** | Archive.org Integration | MEDIUM | MEDIUM
++| **NFR1** | Performance | MEDIUM | MEDIUM
++| **NFR2** | Scalability | MEDIUM | MEDIUM
++| **NFR4** | Security & Privacy | MEDIUM | MEDIUM
++| **NFR5** | Maintainability | MEDIUM | MEDIUM
++| **LOW URGENCY** |||
++| **FR11** | Social Sharing | LOW | LOW
++| **FR12** | Notifications | LOW | LOW
++| **FR49** | A/B Testing | LOW | LOW
++| **FR50** | OSINT Toolkit Integration | LOW | LOW
++| **FR51** | Video Verification System | LOW | LOW
++| **FR52** | Interactive Detection Training | LOW | LOW
++| **FR53** | Cross-Organizational Sharing | LOW | LOW
--Trend: [Graph showing improvement over time]
--{{/code}}
++**Total:** 31 requirements (23 Functional, 8 Non-Functional)
--**2. Hallucination & Faithfulness Metrics**
++**See also:**
++* [[POC Requirements>>FactHarbor.Specification.POC.Requirements]] - POC1 scope and simplifications
++* [[Implementation Roadmap>>FactHarbor.Implementation-Roadmap.WebHome]] - Phase-by-phase implementation plan
++* [[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]] - Foundation that drives these requirements
--**AlignScore (Faithfulness to Evidence):**
--* **Definition:** Measures how well verdicts align with actual evidence content
--* **Scale:** 0-1 (higher is better)
--* **Purpose:** Detect AI hallucinations (making claims not supported by evidence)
--* **Target:** Average ≥0.85, hallucination rate <5%
--* **Display:**
--{{code}}
--Evidence Faithfulness (AlignScore):
--Average: 0.87 ▼ (-0.02 from last month)
++=== 10.1 User Needs Priority ===
--Hallucination Rate: 4.2%
--  - Claims without evidence support: 3.1%
--  - Misrepresented evidence: 1.1%
++User Needs (UN) are the foundation that drives functional and non-functional requirements. They are not independently prioritized; instead, their priority is inherited from the FR/NFR requirements they drive.
--Action: Prompt engineering review scheduled
--{{/code}}
++|= ID |= Title |= Drives Requirements
++| **UN-1** | Trust Assessment at a Glance | Multiple FR/NFR
++| **UN-2** | Claim Extraction and Verification | FR1-7
++| **UN-3** | Article Summary with FactHarbor Analysis Summary | FR4
++| **UN-4** | Social Media Fact-Checking | FR1, FR4
++| **UN-5** | Source Provenance and Track Records | FR6
++| **UN-6** | Publisher Reliability History | FR6
++| **UN-7** | Evidence Transparency | NFR3
++| **UN-8** | Understanding Disagreement and Consensus | FR4
++| **UN-9** | Methodology Transparency | NFR3, NFR11
++| **UN-10** | Manipulation Tactics Detection | FR48
++| **UN-11** | Filtered Research | FR3
++| **UN-12** | Submit Unchecked Claims | FR8
++| **UN-13** | Cite FactHarbor Verdicts | FR10
++| **UN-14** | API Access for Integration | FR13
++| **UN-15** | Verdict Evolution Timeline | FR7
++| **UN-16** | AI vs. Human Review Status | FR9
++| **UN-17** | In-Article Claim Highlighting | FR1
++| **UN-26** | Search Engine Visibility | FR44
++| **UN-27** | Visual Claim Verification | FR46
++| **UN-28** | Safe Contribution Environment | FR48
--**3. Evidence Quality Metrics**
++**Total:** 20 User Needs
--**Source Reliability:**
--* Average source quality score (0-1 scale)
--* Distribution of high/medium/low quality sources
--* Publisher track record trends
++**Note:** Each User Need inherits priority from the requirements it drives. For example, UN-2 (Claim Extraction and Verification) drives FR1-7, which are CRITICAL/HIGH priority, therefore UN-2 is also critical to the project.
--**Evidence Coverage:**
--* Average number of sources per claim
--* Percentage of claims with ≥2 sources (EFCSN minimum)
--* Geographic diversity of sources
++== 11. MVP Scope ==
--**Display:**
--{{code}}
--Evidence Quality:
++**Phase 1 (Months 1-3): Read-Only MVP**
--Average Sources per Claim: 4.2
--Claims with ≥2 sources: 94% (EFCSN compliant)
++Build:
++* Automated claim analysis
++* Confidence scoring
++* Source evaluation
++* Browse/search interface
++* User flagging system
--Source Quality Distribution:
--  High quality (>0.8): 48%
--  Medium quality (0.5-0.8): 43%
--  Low quality (<0.5): 9%
++**Goal**: Prove AI quality before adding user editing
--Geographic Diversity: 23 countries represented
--{{/code}}
++**User Needs fulfilled in Phase 1**: UN-1, UN-2, UN-3, UN-4, UN-5, UN-6, UN-7, UN-8, UN-9, UN-12
--**4. Contributor Consensus Metrics** (when human reviewers involved)
++**Phase 2 (Months 4-6): User Contributions**
--**Inter-Rater Reliability (IRR):**
--* **Calculation:** Cohen's Kappa or Fleiss' Kappa for multiple raters
--* **Scale:** 0-1 (higher is better)
--* **Interpretation:**
--  * >0.8: Almost perfect agreement
--  * 0.6-0.8: Substantial agreement
--  * 0.4-0.6: Moderate agreement
--  * <0.4: Poor agreement
--* **Target:** Maintain ≥0.7 (substantial agreement)
++Add only if needed:
++* Simple editing (Wikipedia-style)
++* Reputation system
++* Basic moderation
++* In-article claim highlighting (FR13)
--**Display:**
--{{code}}
--Contributor Consensus:
++**Additional User Needs fulfilled**: UN-13, UN-17
--Inter-Rater Reliability (IRR): 0.73 (Substantial agreement)
--  - Verdict agreement: 78%
--  - Evidence quality agreement: 71%
--  - Scenario structure agreement: 69%
++**Phase 3 (Months 7-12): Refinement**
--Cases requiring moderator review: 12
--Moderator override rate: 8%
--{{/code}}
++* Continuous quality improvement
++* Feature additions based on real usage
++* Scale infrastructure
-----
++**Additional User Needs fulfilled**: UN-14 (API access), UN-15 (Full evolution tracking)
--==== Quality Dashboard Implementation ====
++**Deferred**:
++* Federation (until multiple successful instances exist)
++* Complex contribution workflows (focus on automation)
++* Extensive role hierarchy (keep simple)
--**Dashboard Location:** `/quality-metrics`
++== 12. Success Metrics ==
--**Update Frequency:**
--* **POC2:** Weekly manual updates
--* **Beta 0:** Daily automated updates
--* **V1.0:** Real-time metrics (updated hourly)
++**System Quality** (track weekly):
++* Error rate by category (target: -10%/month)
++* Average confidence score (target: increase)
++* Source quality distribution (target: more high-quality)
++* Contradiction detection rate (target: increase)
--**Dashboard Sections:**
++**Efficiency** (track monthly):
++* Claims processed per hour (target: increase)
++* Human hours per claim (target: decrease)
++* Automation coverage (target: >90%)
++* Re-work rate (target: <5%)
--1. **Overview:** Key metrics at a glance
--2. **Verdict Quality:** TIGERScore trends and distributions
--3. **Evidence Analysis:** Source quality and coverage
--4. **AI Performance:** Hallucination rates, AlignScore
--5. **Human Oversight:** Contributor consensus, review rates
--6. **System Health:** Processing times, error rates, uptime
++**User Satisfaction** (track quarterly):
++* User flag rate (issues found)
++* Correction acceptance rate (flags valid)
++* Return user rate
++* Trust indicators (surveys)
--**Example Dashboard Layout:**
++**User Needs Metrics** (track quarterly):
++* UN-1: % users who understand trust scores
++* UN-4: Time to verify social media claim (target: <30s)
++* UN-7: % users who access evidence details
++* UN-8: % users who view multiple scenarios
++* UN-15: % users who check evolution timeline
++* UN-17: % users who enable in-article highlighting; avg. time spent on highlighted vs. non-highlighted articles
--{{code}}
--┌─────────────────────────────────────────────────────────────┐
--│ FactHarbor Quality Metrics                    Last updated: │
--│ Public Dashboard                               2 hours ago   │
--└─────────────────────────────────────────────────────────────┘
--
--📊 KEY METRICS
--─────────────────────────────────────────────────────────────
--TIGERScore (Verdict Quality):        84.2 ▲ (+2.1)
--AlignScore (Faithfulness):            0.87 ▼ (-0.02)
--Hallucination Rate:                   4.2% ✓ (Target: <5%)
--Average Sources per Claim:            4.2  ▲ (+0.3)
--
--📈 TRENDS (30 days)
--─────────────────────────────────────────────────────────────
--[Graph: TIGERScore trending upward]
--[Graph: Hallucination rate declining]
--[Graph: Evidence quality stable]
--
--⚠️ IMPROVEMENT TARGETS
--─────────────────────────────────────────────────────────────
--1. Reduce hallucination rate to <3% (Current: 4.2%)
--2. Increase TIGERScore average to >85 (Current: 84.2)
--3. Maintain IRR >0.75 (Current: 0.73)
--
--📄 DETAILED REPORTS
--─────────────────────────────────────────────────────────────
--• Monthly Quality Report (PDF)
--• Methodology Documentation
--• AKEL Performance Analysis
--• Contributor Agreement Analysis
--
--{{/code}}
--
-----
--
--==== Continuous Improvement Feedback Loop ====
--
--**How Metrics Inform AKEL Improvements:**
--
--1. **Identify Weak Areas:**
--   * Low TIGERScore → Review prompt engineering
--   * High hallucination → Strengthen evidence grounding
--   * Low IRR → Clarify evaluation criteria
--
--2. **A/B Testing Integration:**
--   * Test prompt variations
--   * Measure impact on quality metrics
--   * Deploy winners automatically
--
--3. **Alert Thresholds:**
--   * TIGERScore drops below 75 → Alert team
--   * Hallucination rate exceeds 7% → Pause auto-publishing
--   * IRR below 0.6 → Moderator training needed
--
--4. **Monthly Quality Reviews:**
--   * Analyze trends
--   * Identify systematic issues
--   * Plan prompt improvements
--   * Update AKEL models
--
-----
--
--==== Metric Calculation Details ====
--
--**TIGERScore Implementation:**
--* Reference: https://github.com/TIGER-AI-Lab/TIGERScore
--* Input: Generated verdict + reference verdict (from expert)
--* Output: 0-100 score across 5 dimensions
--* Requires: Test set of expert-reviewed claims (minimum 100)
--
--**AlignScore Implementation:**
--* Reference: https://github.com/yuh-zha/AlignScore
--* Input: Generated verdict + source evidence text
--* Output: 0-1 faithfulness score
--* Calculation: Semantic alignment between claim and evidence
--
--**Source Quality Scoring:**
--* Use existing source reliability database (e.g., NewsGuard, MBFC)
--* Factor in: Publication history, corrections record, transparency
--* Scale: 0-1 (weighted average across sources)
--
-----
--
--==== Integration Points ====
--
--* **NFR11: AKEL Quality Assurance** - Metrics validate quality gate effectiveness
--* **FR49: A/B Testing** - Metrics measure test success
--* **FR11: Audit Trail** - Source of quality data
--* **NFR3: Transparency** - Public metrics build trust
--
--**Acceptance Criteria:**
--
--* ✅ All core metrics implemented and calculating correctly
--* ✅ Dashboard updates daily (Beta 0) or hourly (V1.0)
--* ✅ Alerts trigger when metrics degrade beyond thresholds
--* ✅ Monthly quality report auto-generates
--* ✅ Dashboard is publicly accessible (no login required)
--* ✅ Mobile-responsive dashboard design
--* ✅ Metrics inform quarterly AKEL improvement planning
--
--
--
--
  == 13. Requirements Traceability ==
  For full traceability matrix showing which requirements fulfill which user needs, see:
@@ -1234,387 +1234,39 @@
  === FR44: ClaimReview Schema Implementation ===
--**Fulfills:** UN-13 (Cite FactHarbor Verdicts), UN-14 (API Access for Integration), UN-26 (Search Engine Visibility)
++Generate valid ClaimReview structured data for Google/Bing visibility.
--**Phase:** V1.0
--
--**Purpose:** Generate valid ClaimReview structured data for every published analysis to enable Google/Bing search visibility and fact-check discovery.
--
--**Specification:**
--
--==== Component: Schema.org Markup Generator ====
--
--FactHarbor must generate valid ClaimReview structured data following Schema.org specifications for every published claim analysis.
--
--**Required JSON-LD Schema:**
--
--{{code language="json"}}
--{
--  "@context": "https://schema.org",
--  "@type": "ClaimReview",
--  "datePublished": "YYYY-MM-DD",
--  "url": "https://factharbor.org/claims/{claim_id}",
--  "claimReviewed": "The exact claim text",
--  "author": {
--    "@type": "Organization",
--    "name": "FactHarbor",
--    "url": "https://factharbor.org"
--  },
--  "reviewRating": {
--    "@type": "Rating",
--    "ratingValue": "1-5",
--    "bestRating": "5",
--    "worstRating": "1",
--    "alternateName": "FactHarbor likelihood score"
--  },
--  "itemReviewed": {
--    "@type": "Claim",
--    "author": {
--      "@type": "Person",
--      "name": "Claim author if known"
--    },
--    "datePublished": "YYYY-MM-DD if known",
--    "appearance": {
--      "@type": "CreativeWork",
--      "url": "Original claim URL if from article"
--    }
--  }
--}
--{{/code}}
--
--**FactHarbor-Specific Mapping:**
--
--**Likelihood Score to Rating Scale:**
++**Schema.org Mapping:**
  * 80-100% likelihood → 5 (Highly Supported)
--* 60-79% likelihood → 4 (Supported)
--* 40-59% likelihood → 3 (Mixed/Uncertain)
--* 20-39% likelihood → 2 (Questionable)
--* 0-19% likelihood → 1 (Refuted)
++* 60-79% → 4 (Supported)
++* 40-59% → 3 (Mixed)
++* 20-39% → 2 (Questionable)
++* 0-19% → 1 (Refuted)
--**Multiple Scenarios Handling:**
--* If claim has multiple scenarios with different verdicts, generate **separate ClaimReview** for each scenario
--* Add `disambiguatingDescription` field explaining scenario context
--* Example: "Scenario: If interpreted as referring to 2023 data..."
++**Milestone:** V1.0
--==== Implementation Requirements ====
--
--1. **Auto-generate** on claim publication
--2. **Embed** in HTML `<head>` section as JSON-LD script
--3. **Validate** against Schema.org validator before publishing
--4. **Submit** to Google Search Console for indexing
--5. **Update** automatically when verdict changes (integrate with FR8: Time Evolution)
--
--==== Integration Points ====
--
--* **FR7: Automated Verdicts** - Source of rating data and claim text
--* **FR8: Time Evolution** - Triggers schema updates when verdicts change
--* **FR11: Audit Trail** - Logs all schema generation and update events
--
--==== Resources ====
--
--* ClaimReview Project: https://www.claimreviewproject.com
--* Schema.org ClaimReview: https://schema.org/ClaimReview
--* Google Fact Check Guidelines: https://developers.google.com/search/docs/appearance/fact-check
--
--**Acceptance Criteria:**
--
--* ✅ Passes Google Structured Data Testing Tool
--* ✅ Appears in Google Fact Check Explorer within 48 hours of publication
--* ✅ Valid JSON-LD syntax (no errors)
--* ✅ All required fields populated with correct data types
--* ✅ Handles multi-scenario claims correctly (separate ClaimReview per scenario)
--
--
  === FR45: User Corrections Notification System ===
--**Fulfills:** IFCN Principle 5 (Open & Honest Corrections), EFCSN compliance
++Notify users when analyses are corrected.
--**Phase:** Beta 0 (basic), V1.0 (complete) **BLOCKER**
++**Mechanisms:**
++1. In-page banner (30 days)
++2. Public correction log
++3. Email notifications (opt-in)
++4. RSS/API feed
--**Purpose:** When any claim analysis is corrected, notify users who previously viewed the claim to maintain transparency and build trust.
++**Milestone:** Beta 0 (basic), V1.0 (complete) **BLOCKER**
--**Specification:**
--
--==== Component: Corrections Visibility Framework ====
--
--**Correction Types:**
--
--1. **Major Correction:** Verdict changes category (e.g., "Supported" → "Refuted")
--2. **Significant Correction:** Likelihood score changes >20%
--3. **Minor Correction:** Evidence additions, source quality updates
--4. **Scenario Addition:** New scenario added to existing claim
--
--==== Notification Mechanisms ====
--
--**1. In-Page Banner:**
--
--Display prominent banner on claim page:
--
--{{code}}
--[!] CORRECTION NOTICE
--This analysis was updated on [DATE]. [View what changed] [Dismiss]
--
--Major changes:
--• Verdict changed from "Likely True (75%)" to "Uncertain (45%)"
--• New contradicting evidence added from [Source]
--• Scenario 2 updated with additional context
--
--[See full correction log]
--{{/code}}
--
--**2. Correction Log Page:**
--
--* Public changelog at `/claims/{id}/corrections`
--* Displays for each correction:
--  * Date/time of correction
--  * What changed (before/after comparison)
--  * Why changed (reason if provided)
--  * Who made change (AKEL auto-update vs. contributor override)
--
--**3. Email Notifications (opt-in):**
--
--* Send to users who bookmarked or shared the claim
--* Subject: "FactHarbor Correction: [Claim title]"
--* Include summary of changes
--* Link to updated analysis
--
--**4. RSS/API Feed:**
--
--* Corrections feed at `/corrections.rss`
--* API endpoint: `GET /api/corrections?since={timestamp}`
--* Enables external monitoring by journalists and researchers
--
--==== Display Rules ====
--
--* Show banner on **ALL pages** displaying the claim (search results, related claims, embeddings)
--* Banner persists for **30 days** after correction
--* **"Corrections" count badge** on claim card
--* **Timestamp** on every verdict: "Last updated: [datetime]"
--
--==== IFCN Compliance Requirements ====
--
--* Corrections policy published at `/corrections-policy`
--* User can report suspected errors via `/report-error/{claim_id}`
--* Link to IFCN complaint process (if FactHarbor becomes signatory)
--* **Scrupulous transparency:** Never silently edit analyses
--
--==== Integration Points ====
--
--* **FR8: Time Evolution** - Triggers corrections when verdicts change
--* **FR11: Audit Trail** - Source of correction data and change history
--* **NFR3: Transparency** - Public correction log demonstrates commitment
--
--**Acceptance Criteria:**
--
--* ✅ Banner appears within 60 seconds of correction
--* ✅ Correction log is permanent and publicly accessible
--* ✅ Email notifications deliver within 5 minutes
--* ✅ RSS feed updates in real-time
--* ✅ Mobile-responsive banner design
--* ✅ Accessible (screen reader compatible)
--
--
  === FR46: Image Verification System ===
--**Fulfills:** UN-27 (Visual Claim Verification)
++**Methods:**
++1. Reverse image search
++2. EXIF metadata analysis
++3. Manipulation detection (basic)
++4. Context verification
--**Phase:** Beta 0 (basic), V1.0 (extended)
++**Milestone:** Beta 0 (basic), V1.0 (extended)
--**Purpose:** Verify authenticity and context of images shared with claims to detect manipulation, misattribution, and out-of-context usage.
--
--**Specification:**
--
--==== Component: Multi-Method Image Verification ====
--
--**Method 1: Reverse Image Search**
--
--**Purpose:** Find earlier uses of the image to verify context
--
--**Implementation:**
--* Integrate APIs:
--  * **Google Vision AI** (reverse search)
--  * **TinEye** (oldest known uses)
--  * **Bing Visual Search** (broad coverage)
--
--**Process:**
--1. Extract image from claim or user upload
--2. Query multiple reverse search services
--3. Analyze results for:
--   * Earliest known publication
--   * Original context (what was it really showing?)
--   * Publication timeline
--   * Geographic spread
--
--**Output:**
--{{code}}
--Reverse Image Search Results:
--
--Earliest known use: 2019-03-15 (5 years before claim)
--Original context: "Photo from 2019 flooding in Mumbai"
--This claim uses it for: "2024 hurricane damage in Florida"
--
--⚠️ Image is OUT OF CONTEXT
--
--Found in 47 other articles:
--• 2019-03-15: Mumbai floods (original)
--• 2020-07-22: Bangladesh monsoon
--• 2024-10-15: Current claim (misattributed)
--
--[View full timeline]
--{{/code}}
--
-----
--
--**Method 2: AI Manipulation Detection**
--
--**Purpose:** Detect deepfakes, face swaps, and digital alterations
--
--**Implementation:**
--* Integrate detection services:
--  * **Sensity AI** (deepfake detection)
--  * **Reality Defender** (multimodal analysis)
--  * **AWS Rekognition** (face detection inconsistencies)
--
--**Detection Categories:**
--1. **Face Manipulation:**
--   * Deepfake face swaps
--   * Expression manipulation
--   * Identity replacement
--
--2. **Image Manipulation:**
--   * Copy-paste artifacts
--   * Clone stamp detection
--   * Content-aware fill detection
--   * JPEG compression inconsistencies
--
--3. **AI Generation:**
--   * Detect fully AI-generated images
--   * Identify generation artifacts
--   * Check for model signatures
--
--**Confidence Scoring:**
--* **HIGH (80-100%):** Strong evidence of manipulation
--* **MEDIUM (50-79%):** Suspicious artifacts detected
--* **LOW (0-49%):** Minor inconsistencies or inconclusive
--
--**Output:**
--{{code}}
--Manipulation Analysis:
--
--Face Manipulation: LOW RISK (12%)
--Image Editing: MEDIUM RISK (64%)
--  • Clone stamp artifacts detected in sky region
--  • JPEG compression inconsistent between objects
--
--AI Generation: LOW RISK (8%)
--
--⚠️ Possible manipulation detected. Manual review recommended.
--{{/code}}
--
-----
--
--**Method 3: Metadata Analysis (EXIF)**
--
--**Purpose:** Extract technical details that may reveal manipulation or misattribution
--
--**Extracted Data:**
--* **Camera/Device:** Make, model, software
--* **Timestamps:** Original date, modification dates
--* **Location:** GPS coordinates (if present)
--* **Editing History:** Software used, edit count
--* **File Properties:** Resolution, compression, format conversions
--
--**Red Flags:**
--* Metadata completely stripped (suspicious)
--* Timestamp conflicts with claimed date
--* GPS location conflicts with claimed location
--* Multiple edit rounds (hiding something?)
--* Creation date after modification date (impossible)
--
--**Output:**
--{{code}}
--Image Metadata:
--
--Camera: iPhone 14 Pro
--Original date: 2023-08-12 14:32:15
--Location: 40.7128°N, 74.0060°W (New York City)
--Modified: 2024-10-15 08:45:22
--Software: Adobe Photoshop 2024
--
--⚠️ Location conflicts with claim
--Claim says: "Taken in Los Angeles"
--EXIF says: New York City
--
--⚠️ Edited 14 months after capture
--{{/code}}
--
-----
--
--==== Verification Workflow ====
--
--**Automatic Triggers:**
--1. User submits claim with image
--2. Article being analyzed contains images
--3. Social media post includes photos
--
--**Process:**
--1. Extract images from content
--2. Run all 3 verification methods in parallel
--3. Aggregate results into confidence score
--4. Generate human-readable summary
--5. Display prominently in analysis
--
--**Display Integration:**
--
--Show image verification panel in claim analysis:
--
--{{code}}
--📷 IMAGE VERIFICATION
--
--[Image thumbnail]
--
--✅ Reverse Search: Original context verified
--⚠️ Manipulation: Possible editing detected (64% confidence)
--✅ Metadata: Consistent with claim details
--
--Overall Assessment: CAUTION ADVISED
--This image may have been edited. Original context appears accurate.
--
--[View detailed analysis]
--{{/code}}
--
--==== Integration Points ====
--
--* **FR7: Automated Verdicts** - Image verification affects claim credibility
--* **FR4: Analysis Summary** - Image findings included in summary
--* **UN-27: Visual Claim Verification** - Direct fulfillment
--
--==== Cost Considerations ====
--
--**API Costs (estimated per image):**
--* Google Vision AI: $0.001-0.003
--* TinEye: $0.02 (commercial API)
--* Sensity AI: $0.05-0.10
--* AWS Rekognition: $0.001-0.002
--
--**Total per image:** ~$0.07-0.15
--
--**Mitigation Strategies:**
--* Cache results for duplicate images
--* Use free tier quotas where available
--* Prioritize higher-value claims for deep analysis
--* Offer premium verification as paid tier
--
--**Acceptance Criteria:**
--
--* ✅ Reverse image search finds original sources
--* ✅ Manipulation detection accuracy >80% on test dataset
--* ✅ EXIF extraction works for major image formats (JPEG, PNG, HEIC)
--* ✅ Results display within 10 seconds
--* ✅ Mobile-friendly image comparison interface
--* ✅ False positive rate <15%
--
--
  === FR47: Archive.org Integration ===
  Auto-save evidence sources to Wayback Machine.
@@ -1637,6 +1637,7 @@
++**Priority:** HIGH (V1.1)
  **Fulfills:** Advanced media verification
  **Phase:** V1.1
@@ -1651,6 +1651,7 @@
++**Priority:** HIGH (V1.1)
  **Fulfills:** UN-27 (Visual claims), advanced media verification
  **Phase:** V1.1
@@ -1667,6 +1667,7 @@
++**Priority:** MEDIUM (V1.5)
  **Fulfills:** Media literacy education
  **Phase:** V1.5
@@ -1682,6 +1682,7 @@
++**Priority:** MEDIUM (V1.5)
  **Fulfills:** Collaboration with other fact-checkers
  **Phase:** V1.5
@@ -1723,6 +1723,7 @@
++**Priority:** CRITICAL (POC2/Beta)
  **Fulfills:** Accurate evidence counting, quality metrics
  **Phase:** POC2, Beta 0, V1.0

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