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| # Open Privacy Policy Taxonomy (OPPT) |
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| **Advancing privacy policy transparency through open taxonomies and annotated datasets** |
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| ## Mission |
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| We develop standardized frameworks and tools for analyzing privacy policies, enabling researchers and practitioners to: |
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| - Identify dark patterns and deceptive practices in privacy disclosures |
| - Compare privacy practices across companies and sectors |
| - Build machine learning models for automated policy analysis |
| - Track regulatory compliance across jurisdictions |
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| ## Projects |
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| ### OPPT v1.0 Taxonomy |
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| A comprehensive 14-category taxonomy for privacy policy classification, extending the foundational OPP-115 scheme with modern regulatory categories (GDPR, CCPA/CPRA, AI Act). |
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| ### OPPT-T1_C1.0_Section_Jan2026 Dataset |
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| 123 privacy policies from major technology companies annotated using OPPT v1.0, featuring: |
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| - 3,651 annotated segments |
| - Three-model consensus methodology (Claude Haiku 4.5, GPT-5.2, Gemini-3-flash-preview) |
| - Rich attribute schemas |
| - Modern regulatory landscape (January 2026) |
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| **Paper:** [Jurisdiction as Concealment](https://arxiv.org/abs/2601.20792) (arXiv:2601.20792) |
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| ## Research Areas |
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| - Privacy policy analysis and NLP |
| - Dark pattern detection |
| - Regulatory compliance automation |
| - Consumer privacy protection |
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| ## Contact |
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| - **Inquiries**: tebrackin@outlook.com |
| - **Commercial licensing**: tebrackin@outlook.com |
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| *Building tools for a more transparent digital privacy landscape* |
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