Mining4Compliance aims to help organisations share data safely and efficiently by automating compliance with Data Sharing Agreements (DSAs). The project combines ontologies, which formalize rules, roles, and relationships in data sharing, with process mining, which analyses how data flows through real systems. This allows the detection of deviations from agreed policies, identification of potential risks, and enforcement of secure data-sharing practices in real time.

The project addresses common challenges in complex socio-technical environments, such as incomplete or inconsistent data, disconnected policies, and regulatory requirements like GDPR. By transforming DSAs into machine-readable rules, Mining4Compliance enables continuous, automated monitoring of data-sharing activities, reduces the need for manual audits, improves data quality, and provides actionable insights for decision-makers.

The outcome is a practical, intelligent framework that supports secure, compliant, and transparent data sharing, helping organisations manage data responsibly while reducing legal, financial, and reputational risks.

This project is conducted with research partners from the University of Limerick and Dublin City University.