Quick Facts
Sector: Healthcare
Partners: Alfaisal University, D&TA, LabTrace, SDM Diagnostics
Geography: Saudi Arabia
Use Case: Verifiable, privacy-preserving healthcare data exchange
In an age when health systems increasingly rely on data to drive diagnostics, research, and policymaking, the trustworthiness of that data is more than a technical issue—it can be a governmental priority. For Saudi Arabia, whose Vision 2030 charts a course toward a fully digitized, AI-enabled healthcare ecosystem, the question of how to ensure verified, privacy-compliant, and policy-aligned data exchange is both urgent and complex.
This case study presents a pioneering collaboration between Alfaisal University, Labtrace—a UK blockchain technology company borne out of Kings College London, and SDM Diagnostics, which piloted the Data & Trusted AI Alliance (D&TA) data provenance standards in a real-world, regulatory sandbox. Together, the partners designed and tested a blockchain-powered prototype that enabled machine-verifiable provenance of healthcare datasets while maintaining full compliance with Saudi data localization laws and the Personal Data Protection Law (PDPL).
The result was not simply a successful technical test but a demonstration of how Saudi Arabia could build and use scalable, ethical, and globally interoperable data infrastructure for healthcare. It is the first localized use of international provenance standards to certify metadata across institutional boundaries, setting a precedent for trusted cross-border data exchange in alignment with national policy.
The Data Provenance Standards are now being refined into de jure technical standards by the OASIS OPEN standards body, under the sponsorship and leadership of Cisco, IBM, and Microsoft. To learn more, visit: OASIS OPEN DPS and if you would like to reach out to the technical committee with questions or other case studies on data provenance, please email: Kelly Cullinane kelly.cullinane@oasis-open.org