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CRIMEX v2 — Actor Intelligence Dataset

README.md

@@ -12,6 +12,10 @@ configs:
   data_files:
   - split: CrimeX_50k
     path: crimex_v1_la_incident_behavioral_intelligence_sample_50000.csv
+- config_name: CrimeX_actor
+  data_files:
+  - split: actor
+    path: crimex_actor_intelligence.parquet
 tags:
 - crime
 - machine-learning
@@ -20,6 +24,10 @@ tags:
 - behavioral-analysis
 - explainable-ai
 - graph-features
+- law-enforcement
+- intelligence
+- knowledge-graph
+- entity-resolution
 pretty_name: CRIMEX v1 — LA Incident Behavioral Intelligence Dataset
 size_categories:
 - 1M<n<10M
@@ -134,7 +142,219 @@ CRIMEX v1 provides **feature-engineered transformations** and does not modify or
 
 ---
 
-## 🔮 Future Versions
+# CRIMEX v2 — Actor Intelligence Dataset
+
+## 📌 Overview
+
+CRIMEX v2 is a **person-level intelligence dataset** built from public watchlists and criminal data sources.
+
+It extends the CRIMEX framework from incident-level analysis (v1) to **actor-level intelligence modeling**.
+
+The dataset transforms raw OpenSanctions data into:
+
+- Structured actor profiles  
+- Crime-aware intelligence features  
+- Risk scoring and prioritization  
+- Explainable investigation signals  
+
+---
+
+## 📊 Dataset Summary
+
+- **Source:** OpenSanctions Crime Dataset  
+- **Raw records:** 247,463  
+- **Final actor records:** 170,097 :contentReference[oaicite:1]{index=1}  
+- **Total features:** 112 :contentReference[oaicite:2]{index=2}  
+- **Format:** Parquet  
+- **Type:** Tabular intelligence dataset  
+
+---
+
+## 🧠 Feature Categories
+
+### 1. Identity Features
+- Actor name and aliases  
+- Birth date and derived age  
+- Nationality and multi-country indicators  
+- Identity complexity score (aliases + identifiers)  
+
+---
+
+### 2. Crime Intelligence
+- Cleaned crime description  
+- Enhanced crime text extraction  
+- Crime ontology classification:
+  - violent
+  - fraud_identity
+  - narcotics
+  - child_related
+  - other
+  - unknown  
+
+- Serious crime flag  
+- Crime text quality indicators  
+
+---
+
+### 3. Source Intelligence
+- Source dataset name (e.g., INTERPOL, sanctions lists)  
+- Watchlist indicators  
+- Terrorism flag  
+- Source risk score  
+
+---
+
+### 4. Temporal Features
+- First seen / last seen dates  
+- Observation duration  
+- Days since last update  
+- Recent activity indicators  
+
+---
+
+### 5. Geographic Context
+- Country count  
+- Cross-border activity flag  
+- Address-based mobility score  
+
+---
+
+### 6. Risk Scoring
+
+CRIMEX introduces a multi-layer risk system:
+
+- `actor_risk_score_v3` → numerical score  
+- `actor_risk_level_v3` → low / medium / high  
+
+Risk is derived from:
+- crime type
+- source reliability
+- temporal activity
+- identity complexity
+- geographic spread  
+
+---
+
+### 7. Investigator Intelligence
+
+Designed for real-world usage:
+
+- `investigator_priority_level_refined`
+- `investigator_priority_score`
+- `investigator_segment`
+
+Segments include:
+- urgent_high_risk  
+- high_risk_monitor  
+- manual_review  
+- medium_risk_watch  
+- low_risk_archive  
+
+---
+
+### 8. Explainability Layer
+
+Each actor includes human-readable explanations:
+
+- `risk_explanation`
+
+Examples:
+- `serious_crime|watchlist_source|cross_border`
+- `multiple_identities|long_term_activity`
+- `low_signal`
+
+---
+
+### 9. Data Quality Features
+
+- Data completeness score  
+- Missing field indicators  
+- Data confidence score  
+- Sparse data flags  
+
+---
+
+## 🔬 Key Contributions
+
+CRIMEX Actor Intelligence introduces:
+
+- Multi-source actor intelligence modeling  
+- Explainable risk scoring  
+- Separation of **risk vs investigator priority**  
+- Behavioral + contextual + temporal fusion  
+- Analyst-ready feature design  
+
+---
+
+## 🚀 Use Cases
+
+- Criminal risk scoring  
+- Watchlist prioritization  
+- Law enforcement analytics  
+- Graph intelligence systems  
+- Entity resolution and linking  
+- Explainable AI research  
+
+---
+
+## ⚠️ Limitations
+
+- Based on public watchlists (coverage varies by country)  
+- Crime descriptions are partially inferred from source text  
+- Some ontology mapping is rule-based  
+- Not all actors have complete identity data  
+
+---
+
+## ⚖️ Data Source & License
+
+Derived from:
+
+- OpenSanctions  
+  https://www.opensanctions.org  
+
+Important:
+
+- Data is subject to **OpenSanctions license (CC BY-NC 4.0)**  
+- Users must comply with attribution and non-commercial use  
+
+CRIMEX provides **feature-engineered transformations only**.
+
+---
+
+## Reproducibility
+
+The dataset is fully reproducible using:
+
+- Notebook pipeline  
+- Modular Python scripts  
+
+Pipeline modules:
+
+- `src/actor.py`  
+- `src/actor_pipeline.py`  
+- `src/actor_extended.py` :contentReference[oaicite:3]{index=3}  
+
+---
+
+## Files Included
+
+- `crimex_actor_intelligence.parquet` → final dataset  
+- `crimex_actor_feature_dictionary.csv` → feature documentation  
+- `crimex_actor_dataset_metadata.json` → dataset metadata  
+
+---
+
+## Future Work
+
+- Multi-dataset actor linking  
+- Graph-based intelligence networks  
+- Real-time watchlist updates  
+- Integration with CRIMEX v1 (incident + actor fusion)  
+
+---
+
+##  Future Versions
 
 - CRIMEX v2: Geo/POI enrichment using OpenStreetMap (local stack)
 - CRIMEX v3: Multi-source integration (OpenSanctions, Interpol, etc.)

crimex_actor_dataset_metadata.json

@@ -0,0 +1,16 @@
+{
+  "dataset_name": "CRIMEX Actor Intelligence Dataset v2",
+  "source": "OpenSanctions crime dataset",
+  "source_url": "https://data.opensanctions.org/datasets/20260501/crime/targets.simple.csv",
+  "raw_rows": 247463,
+  "final_rows": 170097,
+  "final_columns": 112,
+  "output_file": "C:\\Users\\ayman\\Documents\\IdiomX\\github_idiomX\\CrimeX\\data\\final\\opensanctions\\crimex_actor_intelligence_v2_extended.parquet",
+  "feature_dictionary": "C:\\Users\\ayman\\Documents\\IdiomX\\github_idiomX\\CrimeX\\data\\final\\opensanctions\\crimex_actor_feature_dictionary.csv",
+  "pipeline_modules": [
+    "src/actor.py",
+    "src/actor_pipeline.py",
+    "src/actor_extended.py"
+  ],
+  "license_note": "Derived from OpenSanctions data. Users must comply with OpenSanctions data licensing and attribution requirements."
+}

crimex_actor_feature_dictionary.csv

@@ -0,0 +1,113 @@
+feature_name,data_type,non_null_count,null_count,unique_values,sample_value
+id,object,170097,0,170097,NK-224TRezPqwzhQZ37exWxtX
+schema,object,170097,0,1,Person
+name,object,170097,0,166600,SANAVBARI NIKITENKO
+aliases,object,10299,159798,9313,Michael KUAJIEN DUER MAYOK
+birth_date,object,72098,97999,18175,1992-06-28
+countries,object,166300,3797,575,ru;tj
+addresses,object,94513,75584,40927,"Fayetteville, GA 30214"
+identifiers,object,18827,151270,16484,1538404843
+sanctions,object,170097,0,22758,"""participation in the activity of a terrorist organization; participation in the activity of an illegal armed formation"""
+phones,object,0,170097,0,
+emails,object,0,170097,0,
+program_ids,object,8060,162037,5,INTERPOL-RN
+dataset,object,170097,0,65,INTERPOL Red Notices
+first_seen,object,170097,0,2309,2024-03-04T17:09:51
+last_seen,object,170097,0,27,2026-05-01T00:27:25
+last_change,object,170097,0,857,2025-10-06T18:27:01
+offender_id,object,170097,0,170097,NK-224TRezPqwzhQZ37exWxtX
+offender_name,object,170097,0,166600,SANAVBARI NIKITENKO
+offender_aliases,object,10299,159798,9313,Michael KUAJIEN DUER MAYOK
+offender_birth_date,datetime64[ns],68347,101750,17710,1992-06-28 00:00:00
+offender_nationality_code,object,166300,3797,575,ru;tj
+source_system_code,object,170097,0,1,opensanctions
+source_dataset_name,object,170097,0,65,INTERPOL Red Notices
+source_program_ids,object,8060,162037,5,INTERPOL-RN
+crime_description_raw,object,111868,58229,19354,"""participation in the activity of a terrorist organization"
+crime_description_enhanced,object,80541,89556,11409,"""participation in the activity of a terrorist organization; participation in the activity of an illegal armed formation"""
+crime_text_quality_flag,int32,170097,0,2,1
+has_crime_text_flag,int32,170097,0,2,1
+crime_ontology_code_v3,object,170097,0,6,violent
+crime_ontology_desc_v3,object,170097,0,7,terrorism / armed group activity
+serious_crime_flag_v3,int32,170097,0,2,1
+actor_country_count,int64,170097,0,5,2
+country_context_available_flag,int32,170097,0,2,1
+multi_country_actor_flag,int32,170097,0,2,1
+cross_border_risk_flag,int32,170097,0,2,1
+first_seen_date,datetime64[ns],170097,0,2309,2024-03-04 17:09:51
+last_seen_date,datetime64[ns],170097,0,27,2026-05-01 00:27:25
+last_change_date,datetime64[ns],170097,0,857,2025-10-06 18:27:01
+offender_age_at_first_seen,float64,68347,101750,704,31.7
+offender_age_group,object,170097,0,5,adult
+has_birth_date_flag,int32,170097,0,2,1
+alias_count,int64,170097,0,29,0
+has_alias_flag,int32,170097,0,2,0
+has_multiple_aliases_flag,int32,170097,0,2,0
+identifier_count,int64,170097,0,12,0
+has_identifier_flag,int32,170097,0,2,0
+has_multiple_ids_flag,int32,170097,0,2,0
+identity_complexity_score,int64,170097,0,32,0
+address_count,int64,170097,0,8,0
+has_address_flag,int32,170097,0,2,0
+multi_address_flag,int32,170097,0,2,0
+phone_count,int64,170097,0,1,0
+email_count,int64,170097,0,1,0
+has_phone_flag,int32,170097,0,1,0
+has_email_flag,int32,170097,0,1,0
+contact_traceability_score,int32,170097,0,1,0
+geo_mobility_score,int64,170097,0,10,2
+dataset_lower,object,170097,0,65,interpol red notices
+is_interpol_flag,int32,170097,0,2,1
+is_wanted_flag,int32,170097,0,2,0
+is_terrorism_flag,int32,170097,0,2,0
+is_sanctions_flag,int32,170097,0,1,0
+program_count,int64,170097,0,2,1
+has_program_flag,int32,170097,0,2,1
+interpol_red_notice_flag,int32,170097,0,2,1
+source_count,int64,170097,0,4,1
+multi_source_flag,int32,170097,0,2,0
+source_risk_score,int32,170097,0,5,5
+actor_observed_days,int64,170097,0,797,787
+long_observed_actor_flag,int32,170097,0,2,1
+days_since_last_change,int64,170097,0,334,206
+recently_changed_actor_flag,int32,170097,0,2,0
+data_completeness_score,int32,170097,0,4,1
+crime_text_length,int64,170097,0,545,120
+crime_text_word_count,int64,170097,0,146,17
+identity_score,int64,170097,0,6,0
+geo_score,int64,170097,0,6,2
+temporal_score,int32,170097,0,3,1
+actor_risk_score_v3,float64,170097,0,38,14.0
+actor_risk_level_v3,object,170097,0,3,high
+risk_driver_crime_flag,int32,170097,0,2,1
+risk_driver_source_flag,int32,170097,0,2,1
+risk_driver_geo_flag,int32,170097,0,2,1
+risk_driver_identity_flag,int32,170097,0,2,0
+risk_driver_temporal_flag,int32,170097,0,2,1
+risk_explanation,object,170097,0,24,serious_crime|watchlist_source|cross_border|long_term_activity
+normalized_name,object,170097,0,162573,sanavbari nikitenko
+potential_duplicate_count,int64,170097,0,11,1
+is_potential_duplicate_flag,int32,170097,0,2,0
+terrorism_flag,int32,170097,0,2,1
+financial_crime_flag,int32,170097,0,2,0
+recent_high_risk_flag,int32,170097,0,2,0
+data_confidence_score,int64,170097,0,13,2
+investigator_priority_score,float64,170097,0,41,31.0
+investigator_priority_level_refined,object,170097,0,3,high
+has_rich_crime_text_flag,int32,170097,0,2,1
+short_crime_text_flag,int32,170097,0,2,0
+alias_identifier_ratio,float64,170097,0,40,0.0
+identity_density_score,int64,170097,0,32,1
+high_identity_density_flag,int32,170097,0,2,0
+address_country_ratio,float64,170097,0,12,0.0
+high_geo_complexity_flag,int32,170097,0,2,1
+short_observed_actor_flag,int32,170097,0,2,0
+very_long_observed_actor_flag,int32,170097,0,2,1
+stale_record_flag,int32,170097,0,2,0
+strong_source_signal_flag,int32,170097,0,2,1
+weak_source_signal_flag,int32,170097,0,2,0
+risk_priority_mismatch_flag,int32,170097,0,1,0
+needs_manual_review_flag,int32,170097,0,2,0
+core_identity_available_score,int32,170097,0,3,3
+data_sparse_flag,int32,170097,0,2,0
+investigator_segment,object,170097,0,5,high_risk_monitor

crimex_actor_intelligence.parquet

@@ -0,0 +1,3 @@
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+size 23857667