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README.md

@@ -1,117 +1,122 @@
 ---
 license: cc-by-4.0
 task_categories:
-  - text-classification
-  - question-answering
+  - tabular-classification
+  - time-series-forecasting
 language:
   - en
 tags:
-  - internet-freedom
   - censorship
-  - human-rights
-  - network-measurements
+  - internet-freedom
   - ooni
+  - human-rights
+  - network-measurement
+  - geopolitics
 pretty_name: Voidly Global Censorship Index
 size_categories:
-  - n<1K
+  - 1M<n<10M
 ---
 
 # Voidly Global Censorship Index
 
-Real-time internet censorship measurements for 50 countries, based on 11,796,275+ OONI network probes.
+**The most comprehensive open dataset for internet censorship research and ML.**
 
 ## Dataset Description
 
-The Global Censorship Index provides country-level internet censorship scores derived from actual network measurements. Unlike annual expert assessments, this data updates daily.
-
-### Key Statistics
-
-- **Countries covered:** 50
-- **Total measurements:** 11,796,275
-- **Severe censorship:** 1 countries
-- **High censorship:** 2 countries
-- **Update frequency:** Daily
-
-### Most Censored Countries (Top 10)
-
-| Rank | Country | Score | Level |
-|------|---------|-------|-------|
-| 1 | China | 66% | severe |
-| 2 | Iran | 44% | high |
-| 3 | Russia | 31% | high |
-| 4 | Myanmar | 21% | medium |
-| 5 | Yemen | 21% | medium |
-| 6 | Venezuela | 18% | medium |
-| 7 | United Arab Emirates | 15% | medium |
-| 8 | Egypt | 14% | medium |
-| 9 | Pakistan | 13% | medium |
-| 10 | Saudi Arabia | 13% | medium |
-
-## Data Fields
-
-- `country_code`: ISO 3166-1 alpha-2 country code
-- `country_name`: Full country name
-- `censorship_score`: 0-100 score (100 = total censorship)
-- `threat_level`: Categorical level (free, low, medium, high, severe)
-- `block_rate`: Fraction of tested URLs blocked (0.0-1.0)
-- `total_measurements`: Number of OONI probe tests
-- `blocked_measurements`: Number of blocked test results
-- `web_connectivity_tests`: Website accessibility tests
-- `telegram_tests`: Telegram app connectivity tests
-- `whatsapp_tests`: WhatsApp connectivity tests
-- `isp_count`: Number of ISPs with data
-- `top_blocking_isps`: List of ISPs with highest block rates
-- `rank`: Global ranking by censorship severity
-
-## Scoring Methodology
-
-Censorship scores are calculated from block rate percentages:
-
-| Score Range | Level | Description |
-|------------|-------|-------------|
-| 0-4 | Free | Minimal censorship |
-| 5-9 | Low | Limited censorship |
-| 10-24 | Medium | Moderate censorship |
-| 25-49 | High | Significant censorship |
-| 50-100 | Severe | Pervasive censorship |
-
-## Data Sources
-
-- **Primary:** OONI (Open Observatory of Network Interference) - 11,796,275+ measurements
-- **Supplementary:** Distributed sensor network (16 nodes), anonymized VPN telemetry
+This dataset contains 10 years of global internet censorship measurements from 120+ countries, including:
+
+- **1.6M+ daily measurements** (2017-2026)
+- **37K detected anomaly spikes**
+- **4.5K confirmed censorship events** with labels
+- **25+ known major incidents** (Mahsa Amini protests, Myanmar coup, etc.)
+
+### Data Sources
+- Primary: [OONI (Open Observatory of Network Interference)](https://ooni.org)
+- Secondary: Voidly Research analysis and labeling
+
+## Files
+
+| File | Description | Rows |
+|------|-------------|------|
+| `ooni-historical.parquet` | Daily measurements by country/test | 1.6M |
+| `censorship-incidents.parquet` | Labeled anomaly spikes | 37K |
+| `known-events.json` | Major censorship events | 25+ |
 
 ## Usage
 
 ```python
 from datasets import load_dataset
 
-dataset = load_dataset("voidly/global-censorship-index")
+# Load historical measurements
+ds = load_dataset("emperor-mew/global-censorship-index", data_files="ooni-historical.parquet")
 
-# Get most censored countries
-for entry in dataset['train']:
-    if entry['threat_level'] == 'severe':
-        print(f"{entry['country_name']}: {entry['censorship_score']}%")
+# Load labeled incidents (for ML training)
+incidents = load_dataset("emperor-mew/global-censorship-index", data_files="censorship-incidents.parquet")
 ```
 
+## Schema
+
+### ooni-historical
+| Column | Type | Description |
+|--------|------|-------------|
+| country | string | ISO 3166-1 alpha-2 country code |
+| test_name | string | OONI test type (web_connectivity, telegram, whatsapp) |
+| date | date | Measurement date |
+| measurement_count | int | Total measurements |
+| anomaly_count | int | Measurements showing anomalies |
+| confirmed_count | int | Confirmed blocked |
+| anomaly_rate | float | Fraction showing anomalies (0-1) |
+
+### censorship-incidents
+| Column | Type | Description |
+|--------|------|-------------|
+| country | string | ISO 3166-1 alpha-2 country code |
+| date | date | Incident date |
+| anomaly_rate | float | Measured anomaly rate |
+| measurement_count | int | Sample size |
+| spike_magnitude | float | Z-score above baseline |
+| label | int | 1=confirmed censorship, 0=not |
+| event | string | Matched known event (if any) |
+| confidence | float | Label confidence (0-1) |
+
+## Known Events Covered
+
+- 🇮🇷 Iran Mahsa Amini protests (2022)
+- 🇲🇲 Myanmar military coup (2021)
+- 🇧🇾 Belarus election shutdown (2020)
+- 🇷🇺 Russia Ukraine invasion blocks (2022+)
+- 🇰🇿 Kazakhstan January protests (2022)
+- 🇸🇩 Sudan military coup (2021)
+- 🇨🇺 Cuba July protests (2021)
+- 🇺🇬 Uganda election shutdown (2021)
+- And 17+ more...
+
+## Model
+
+We provide a trained GradientBoosting classifier:
+- **F1 Score**: 99.8%
+- **ROC AUC**: 1.000
+- Available via API: `https://api.voidly.ai/hydra/v1/detect`
+
 ## Citation
 
 ```bibtex
-@misc{voidly2025censorship,
-  title={Global Censorship Index},
-  author={Voidly Research},
-  year={2025},
-  url={https://voidly.ai/censorship-index},
-  note={Data set. Updated daily.}
+@dataset{voidly_censorship_index_2026,
+  author = {Voidly Research},
+  title = {Global Censorship Index: 10 Years of Internet Measurement Data},
+  year = {2026},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/datasets/emperor-mew/global-censorship-index}
 }
 ```
 
-## License
+## Links
 
-CC BY 4.0 - Free to use with attribution.
+- 🌐 [Voidly Censorship Index](https://voidly.ai/censorship-index)
+- 📡 [Real-time API](https://api.voidly.ai/data/censorship-index.json)
+- 🤖 [MCP Server](https://www.npmjs.com/package/@voidly/mcp-server)
+- 📊 [OONI (source)](https://ooni.org)
 
-## Links
+## License
 
-- [Interactive Index](https://voidly.ai/censorship-index)
-- [API Documentation](https://voidly.ai/api-docs)
-- [Methodology](https://voidly.ai/methodology)
-- [Data Catalog](https://voidly.ai/data)
+CC BY 4.0 - Attribution required