CIA Platform Data Repository

This directory contains CSV data files downloaded from the CIA Platform for use in Riksdagsmonitor dashboards.

📊 Data Quality Upgrade (2026-02-18)

Comprehensive CIA Intelligence Data Integration

• ✅ 69 total files (was 36)
• ✅ 33 new files added: Risk views, anomaly detection, percentile time-series, committee data
• ✅ 403 real politicians with complete risk assessment (was 3 aggregated rows)
• ✅ All files validated: 0 errors, 0 warnings
• ✅ Mock data removed: Dashboards now use authentic CIA Platform intelligence

Key Improvements

1. Risk Assessment: 69KB detailed politician risk data (403 MPs × 45 rules)
2. Anomaly Detection: 13KB seasonal patterns + voting anomaly detection
3. Temporal Analysis: 23 percentile files for trend visualization
4. Committee Intelligence: 2.8MB of committee decision data (10,000+ records)
5. Data Validation: Automated validation script ensures quality

Purpose

• Improved Performance: Local data loading is faster than remote fetches
• Reliability: Reduces dependency on external network availability
• Offline Capability: Dashboards work even without internet connection
• Development: Enables local testing without API rate limits
• Data Quality: Real CIA Platform intelligence (no synthetic mock data)

Directory Structure

cia-data/
├── README.md                                      # This file
├── data-manifest.json                             # File metadata (v2.0)
├── download-csv.sh                                # Automated download (69 files)
├── validate-csv.sh                                # Data validation script
│
├── risk/                                          # Risk Assessment (69KB)
│   ├── distribution_ministry_risk_levels.csv     # Ministry risk aggregation (91 bytes)
│   ├── distribution_ministry_risk_quarterly.csv  # Quarterly trends (405 bytes)
│   ├── distribution_crisis_resilience.csv        # Crisis resilience (441 bytes)
│   ├── view_politician_risk_summary_sample.csv   # 403 politicians (69KB) ★
│   ├── view_ministry_risk_evolution_sample.csv   # Ministry temporal risk (1.8KB)
│   └── view_risk_score_evolution_sample.csv      # Risk evolution (5.5KB)
│
├── anomaly/                                       # Anomaly Detection (13KB)
│   ├── distribution_anomaly_by_party.csv         # Party anomaly patterns (61 bytes)
│   ├── view_riksdagen_voting_anomaly_detection_sample.csv      # Voting anomalies (197 bytes)
│   ├── view_riksdagen_seasonal_anomaly_detection_sample.csv    # Seasonal patterns (13KB) ★
│   └── view_election_cycle_anomaly_pattern_sample.csv          # Election cycle anomalies (4.1KB)
│
├── percentile/                                    # Temporal Analysis (23 files)
│   ├── percentile_risk_score_evolution.csv       # Risk percentiles
│   ├── percentile_voting_anomaly_detection.csv   # Anomaly percentiles
│   ├── percentile_crisis_resilience_indicators.csv
│   ├── percentile_seasonal_activity_patterns.csv
│   ├── percentile_committee_productivity*.csv    # Committee percentiles (2 files)
│   ├── percentile_ministry_*.csv                 # Ministry percentiles (4 files)
│   ├── percentile_party_*.csv                    # Party percentiles (3 files)
│   ├── percentile_politician_*.csv               # Politician percentiles (8 files)
│   └── percentile_election_proximity_trends.csv
│
├── committee/                                     # Committee Data (2.8MB)
│   ├── distribution_committee_activity.csv
│   ├── distribution_committee_productivity.csv
│   ├── distribution_committee_productivity_matrix.csv
│   ├── distribution_annual_committee_assignments.csv
│   ├── distribution_annual_committee_documents.csv
│   ├── view_riksdagen_committee_decisions_sample.csv                  # 1.1MB, 5,006 records ★
│   └── view_riksdagen_committee_ballot_decision_party_summary_sample.csv # 1.7MB, 5,028 records ★
│
├── party/                                         # Party Performance
│   ├── distribution_party_performance.csv
│   ├── distribution_party_effectiveness_trends.csv
│   ├── distribution_party_momentum.csv
│   ├── distribution_coalition_alignment.csv
│   ├── distribution_annual_party_members.csv
│   ├── distribution_gender_by_party.csv
│   ├── distribution_experience_by_party.csv
│   ├── distribution_behavioral_patterns_by_party.csv
│   └── distribution_decision_patterns_by_party.csv
│
├── politician/                                    # Politician Data
│   ├── distribution_experience_levels.csv
│   ├── distribution_assignment_roles.csv
│   ├── distribution_influence_buckets.csv
│   └── distribution_person_status.csv
│
├── ministry/                                      # Ministry Effectiveness
│   ├── distribution_ministry_effectiveness.csv
│   ├── distribution_ministry_productivity_matrix.csv
│   ├── distribution_ministry_decision_impact.csv
│   └── distribution_annual_ministry_assignments.csv
│
├── voting/                                        # Voting & Ballot Data
│   ├── distribution_annual_party_votes.csv
│   ├── distribution_annual_ballots.csv
│   ├── distribution_decision_trends.csv
│   ├── distribution_document_types.csv
│   ├── distribution_annual_document_types.csv
│   ├── distribution_document_status.csv
│   └── distribution_annual_document_status.csv
│
├── election/                                      # Election Data
│   └── distribution_election_regions.csv
│
├── election-cycle/                                # Election Cycle Analysis
│   ├── view_election_cycle_comparative_analysis_sample.csv
│   ├── view_election_cycle_decision_intelligence_sample.csv
│   ├── view_election_cycle_predictive_intelligence_sample.csv
│   └── view_election_cycle_temporal_trends_sample.csv
│
├── seasonal/                                      # Seasonal Activity
│   └── view_riksdagen_seasonal_activity_patterns_sample.csv
│
└── Root-Level Files                               # Large detailed datasets
    ├── view_riksdagen_politician_sample.csv                      # 540KB
    ├── view_riksdagen_politician_experience_summary_sample.csv   # 5.7MB
    ├── view_riksdagen_party_summary_sample.csv                   # 3.6KB
    ├── view_riksdagen_party_role_member_sample.csv               # 42KB
    ├── view_riksdagen_party_document_summary_sample.csv          # 1.5KB
    ├── view_riksdagen_committee_decisions.csv                    # 111KB (existing)
    ├── view_riksdagen_committee_ballot_decision_party_summary.csv # 172KB (existing)
    └── extraction_summary_report.csv                             # 16KB

★ = New high-value files added in 2026-02-18 upgrade

Data Files

Election Cycle Data (election-cycle/)

1. view_election_cycle_comparative_analysis_sample.csv

Size: ~153KB | Records: 1,110+
Dashboard: Election Cycle Intelligence Dashboard
Purpose: Party performance evolution across 9 election cycles (1994-2034)

Key Fields:

• election_cycle_id: Election cycle identifier (e.g., "2022-2026")
• cycle_year: Cycle numeric identifier
• calendar_year: Specific year within cycle
• semester: Time period (annual, spring, autumn)
• party: Political party abbreviation (M, S, SD, C, V, MP, KD, L)
• performance_score: Overall performance metric (0-100)
• party_win_rate: Win percentage in votes (0-100)
• party_participation_rate: Participation percentage
• discipline_score: Party discipline metric
• rank_by_performance: Performance ranking
• ntile_party_tier: Performance tier (1-4, 1=best)
• competitiveness_index: Competitiveness metric
• change_performance_pct: Performance change percentage
• performance_trend: Trend indicator (stable, improving, declining)

Use Cases:

• Timeline chart showing party performance evolution
• Party tier distribution analysis
• Historical trend comparison
• Performance ranking visualization

---

2. view_election_cycle_decision_intelligence_sample.csv

Size: ~59KB | Records: 414+
Dashboard: Election Cycle Intelligence Dashboard
Purpose: Legislative decision-making effectiveness by party and cycle

Key Fields:

• election_cycle_id: Election cycle identifier
• party: Political party abbreviation
• total_proposals: Number of proposals submitted
• approved_proposals: Number approved
• rejected_proposals: Number rejected
• avg_approval_rate: Average approval rate percentage
• decision_effectiveness: Effectiveness category (LOWLY_EFFECTIVE, MODERATELY_EFFECTIVE, HIGHLY_EFFECTIVE)
• legislative_momentum: Momentum score
• ministry_impact_score: Ministry impact metric (0-100)
• ministries_with_decisions: Count of ministries involved
• rank_by_success_rate: Success ranking
• ntile_effectiveness: Effectiveness quartile (1-4)
• change_success_pct: Success rate change percentage
• decision_trend: Trend indicator

Use Cases:

• Decision effectiveness heatmap (D3.js)
• Approval rate analysis by party/cycle
• Legislative momentum tracking
• Ministry impact assessment

---

3. view_election_cycle_predictive_intelligence_sample.csv

Size: ~3.9KB | Records: 41+
Dashboard: Election Cycle Intelligence Dashboard
Purpose: Predictive risk forecasting and early warning indicators

Key Fields:

• election_cycle_id: Election cycle identifier
• semester: Time period
• risk_forecast_category: Risk level (STABLE, RAPID_ESCALATION)
• politicians_at_risk: Count of politicians at risk
• avg_risk_score_change: Average risk score change
• ministries_at_risk: Count of ministries at risk
• avg_party_win_rate_trend: Average win rate trend
• parties_with_increasing_absence: Count of parties with rising absences
• risk_trajectory: Risk trajectory indicator
• forecast_confidence: Confidence level (low, moderate, high)
• predictive_alert_level: Alert level (low, medium, high)

Use Cases:

• Risk forecast scatter chart
• Early warning system visualization
• Risk trajectory analysis
• Confidence interval display

---

4. view_election_cycle_temporal_trends_sample.csv

Size: ~8.7KB | Records: 74+
Dashboard: Election Cycle Intelligence Dashboard
Purpose: Temporal voting patterns and activity trends

Key Fields:

• election_cycle_id: Election cycle identifier
• semester: Time period
• is_pre_election_semester: Boolean indicator
• months_until_election: Months remaining until election
• active_politicians: Count of active MPs
• avg_attendance_rate: Average attendance percentage
• total_ballots: Total ballot count
• total_votes: Total votes cast
• avg_win_rate: Average win rate
• avg_rebel_rate: Average rebellion rate
• violation_count: Rule violation count
• total_decisions: Total decisions made
• avg_approval_rate: Average approval rate
• avg_committee_productivity: Committee productivity metric
• stddev_attendance: Attendance standard deviation
• stddev_win_rate: Win rate standard deviation
• volatility_assessment: Volatility indicator (stable, moderate, high)
• change_attendance_pct: Attendance change percentage
• change_decisions_pct: Decision volume change percentage
• forecast_trend: Forecast trend indicator

Use Cases:

• Temporal trends multi-axis chart
• Pre-election period analysis
• Activity pattern visualization
• Volatility assessment

---

Data Source

All data files are sourced from the CIA platform sample data repository:

https://github.com/Hack23/cia/tree/master/service.data.impl/sample-data

Base URL: https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/

Updating Data

To update all CSV files, run the download script:

cd cia-data
chmod +x download-csv.sh
./download-csv.sh

Or manually download specific files:

cd cia-data/election-cycle
curl -O https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/view_election_cycle_comparative_analysis_sample.csv
curl -O https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/view_election_cycle_decision_intelligence_sample.csv
curl -O https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/view_election_cycle_predictive_intelligence_sample.csv
curl -O https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/view_election_cycle_temporal_trends_sample.csv

Dashboard Integration

Election Cycle Dashboard

File: js/election-cycle-dashboard.js
Strategy: Local-first with remote fallback

The dashboard attempts to load data from local files first, then falls back to remote GitHub URLs if local files are unavailable:

const CONFIG = {
  dataUrls: {
    comparative: [
      'cia-data/election-cycle/view_election_cycle_comparative_analysis_sample.csv',
      'https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/view_election_cycle_comparative_analysis_sample.csv'
    ],
    // ... other files
  }
};

Data Freshness

• Update Frequency: Sample data is relatively static
• Last Updated: 2026-02-09
• Recommended Update: Monthly or when CIA platform releases updates

Size Information

Total size: ~225KB (4 CSV files)

File	Size	Records
comparative_analysis	153KB	1,110+
decision_intelligence	59KB	414+
predictive_intelligence	3.9KB	41+
temporal_trends	8.7KB	74+

Data Quality

All CSV files include:

• ✅ Header row with field names
• ✅ Comma-separated values
• ✅ UTF-8 encoding
• ✅ Consistent date formats
• ✅ Numeric values properly formatted

Related Documentation

• ELECTION_CYCLE_DASHBOARD.md - Dashboard implementation guide
• CIA Platform - Source repository
• Riksdagsmonitor README - Project overview

License

Data is provided by the CIA platform under Apache License 2.0.

Contributing

To add new data files:

1. Download from CIA platform sample-data directory
2. Place in appropriate subdirectory
3. Update this README with file description
4. Update download-csv.sh script
5. Commit both CSV and documentation

---

Maintained by: Hack23 AB
Last Updated: 2026-02-09

Data Sources

All CSV files are downloaded from:

https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/

Usage Pattern

Dashboards implement a local-first loading strategy:

1. Try Local: Attempt to load from cia-data/ directory
2. Fallback Remote: If local unavailable, fetch from GitHub
3. Cache: Store in browser LocalStorage for 24 hours

Example configuration:

const CONFIG = {
  dataUrls: [
    'cia-data/seasonal/view_riksdagen_seasonal_activity_patterns_sample.csv',  // Local
    'https://raw.githubusercontent.com/Hack23/cia/master/service.data.impl/sample-data/view_riksdagen_seasonal_activity_patterns_sample.csv'  // Remote
  ]
};

Updating Data

To refresh all CSV files:

cd cia-data
./download-csv.sh

This script downloads the latest data from the CIA platform repository.

Data Categories

Seasonal Activity Patterns (seasonal/)

Quarterly parliamentary activity analysis (2002-2025):

• File: view_riksdagen_seasonal_activity_patterns_sample.csv
• Records: 85 (11 quarters missing from full 96-quarter coverage for 2002–2025)
• Dashboard: Seasonal Activity Patterns Dashboard
• Fields: 32 columns including:
  • Time dimensions: year, quarter, is_election_year, election_cycle
  • Activity metrics: total_ballots, active_politicians, attendance_rate, documents_produced
  • Baselines: q_baseline_ballots, q_baseline_docs, q_baseline_attendance
  • Statistical: ballot_z_score, doc_z_score, attendance_z_score (anomaly detection)
  • Classifications: base_activity_classification, seasonal_pattern_classification
  • Cross-year: cross_year_quarter_avg_ballots, cross_year_z_score
  • Trends: qoq_ballot_change_pct, activity_quartile_cycle

Anomaly Detection (seasonal/)

Statistical outlier identification in parliament activity (2002-2026):

• File: view_riksdagen_seasonal_anomaly_detection_sample.csv
• Records: 41 quarters (2002 Q1 - 2026 Q1)
• Dashboard: Anomaly Detection & Early Warning System
• Purpose: Identify unusual parliamentary activity patterns using Z-score analysis
• Fields: 20 columns including:
  • Time dimensions: year, quarter, is_election_year, parliamentary_period
  • Activity metrics: total_ballots, active_politicians, attendance_rate, documents_produced
  • Baselines: q_baseline_ballots, q_baseline_docs, q_baseline_attendance
  • Std Deviations: q_stddev_ballots, q_stddev_docs, q_stddev_attendance
  • Z-Scores: ballot_z_score, doc_z_score, attendance_z_score
  • Classification: activity_classification, anomaly_type, anomaly_direction
  • Severity: max_z_score, anomaly_severity (LOW, MODERATE, HIGH, CRITICAL)
  • Labels: quarter_label (Q1_JAN_MAR, Q2_APR_JUN, Q3_JUL_SEP, Q4_OCT_DEC)

Anomaly Detection Criteria:

• |Z| < 1.5: LOW severity (within normal range)
• 1.5 ≤ |Z| < 2.0: MODERATE severity
• 2.0 ≤ |Z| < 2.5: HIGH severity
• |Z| ≥ 2.5: CRITICAL severity

Historical Findings (from 41 quarters):

• 8 CRITICAL anomalies (Z ≥ 2.5)
• 2 HIGH anomalies (2.0 ≤ Z < 2.5)
• 12 MODERATE anomalies (1.5 ≤ Z < 2.0)
• 19 LOW (normal activity)
• Most extreme: 2006 Q1 document anomaly (Z = +10.97)

Data Quality

• Validation: All CSV files validated against CIA platform schemas
• Completeness: Sample data represents key patterns and trends
• Updates: Data refreshed periodically from CIA platform
• Integrity: Files include checksums in data-manifest.json

New High-Value Datasets (2026-02-18)

Risk Assessment - view_politician_risk_summary_sample.csv

Size: 69KB | Records: 403 politicians
Dashboard: Risk Assessment Dashboard (js/risk-dashboard.js)
Source: CIA Platform 45-rule risk scoring engine

Purpose: Complete risk assessment for all 403 current Swedish MPs with detailed violation tracking and risk classification.

Key Fields:

• person_id: Unique politician identifier
• first_name, last_name, party: Politician details
• status: Current status (e.g., "Tjänstgörande riksdagsledamot")
• total_violations: Total number of policy/conduct violations
• latest_violation_date: Most recent violation timestamp
• absenteeism_violations, effectiveness_violations, discipline_violations, productivity_violations, collaboration_violations: Violation breakdowns
• annual_absence_rate: Annual absence percentage
• annual_rebel_rate: Annual rebellion rate percentage
• annual_vote_count: Total votes cast annually
• documents_last_year: Documents produced in last year
• risk_score: Overall risk score (0-100 scale)
• risk_level: Classification (LOW, MEDIUM, HIGH, CRITICAL)
• risk_assessment: Textual assessment summary

Heat Map Transformation: Each politician generates 45 data points: 403 politicians × 45 rules = 18,135 risk assessment data points

Anomaly Detection - view_riksdagen_seasonal_anomaly_detection_sample.csv

Size: 13KB | Records: 42 seasonal patterns
Purpose: Detect unusual parliamentary activity using z-score statistical analysis

Key Fields:

• ballot_z_score, doc_z_score, attendance_z_score: Statistical deviations
• anomaly_type: NO_ANOMALY, DOCUMENT_ANOMALY, etc.
• anomaly_severity: LOW, CRITICAL, etc.

Committee Intelligence Files

view_riksdagen_committee_decisions_sample.csv: 1.1MB, 5,006 decisions
view_riksdagen_committee_ballot_decision_party_summary_sample.csv: 1.7MB, 5,028 party votes

Purpose: Complete committee decision tracking with party voting patterns

Data Validation

Run validation: ./cia-data/validate-csv.sh

Checks: UTF-8/ASCII encoding, CSV structure, file sizes, column consistency

Dashboard → CSV Mapping

Dashboard	Primary CSV Files
Risk Assessment	risk/view_politician_risk_summary_sample.csv (403 politicians)
Committee	committee/view_riksdagen_committee_decisions_sample.csv (5,006 records)
Coalition	party/distribution_coalition_alignment.csv
Ministry	risk/view_ministry_risk_evolution_sample.csv

License

Data sourced from CIA Platform (Citizen Intelligence Agency):

• Repository: https://github.com/Hack23/cia
• License: Apache License 2.0
• Copyright: © 2008-2026 Hack23 AB

Support

For questions about the data or CIA platform:

• Website: https://www.hack23.com/cia
• Documentation: https://hack23.github.io/cia/
• Issues: https://github.com/Hack23/cia/issues

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Last Updated: 2026-02-18
Maintained by: Hack23 AB