# Machine Understandable Policies and GDPR Compliance Checking

arXiv: https://arxiv.org/abs/2001.08930 · HTML: https://mlsanity.com/paper/2001.08930/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jan 2020.

## Built on by (most cited first, 3 of 3)

- [A Human-in-the-Loop Approach for Information Extraction from Privacy Policies under Data Scarcity](https://mlsanity.com/paper/2305.15006/) (2023)
- [Towards Computer-Using Personal Agents](https://mlsanity.com/paper/2503.15515/) (2025)
- [Axis-Aligned Semantics for ODRL: Resolving Dimensional Ambiguity in Policy Constraints](https://mlsanity.com/paper/2602.19878/) (2026)

## Abstract (arXiv)

The European General Data Protection Regulation (GDPR) calls for technical and organizational measures to support its implementation. Towards this end, the SPECIAL H2020 project aims to provide a set of tools that can be used by data controllers and processors to automatically check if personal data processing and sharing complies with the obligations set forth in the GDPR. The primary contributions of the project include: (i) a policy language that can be used to express consent, business policies, and regulatory obligations; and (ii) two different approaches to automated compliance checking that can be used to demonstrate that data processing performed by data controllers / processors complies with consent provided by data subjects, and business processes comply with regulatory obligations set forth in the GDPR.