SPECIAL is a H2020-funded project that aims at creating a scalable policy-aware linked data architecture for privacy, transparency and compliance.
We develop technology that:
- supports the acquisition of user consent at collection time and the recording of both data and metadata (consent policies, event data, context) according to legislative and user-specified policies;
- caters for privacy-aware, secure workflows that include usage/access control, transparency and compliance verification;
- demonstrates robustness in terms of performance, scalability and security, all of which are necessary to support privacy preserving innovation in Big Data environments; and
- provides a dashboard with feedback and control features that make privacy in Big Data comprehensible and manageable for data subjects, controllers, and processors.
SPECIAL aims at making its research and development work publicly accessible. Here, you will find our github repository with software code we developed within the project.