Enhancing controlled query evaluation through epistemic policies

In an era where data privacy is paramount, the challenge of sharing information without compromising sensitive details has become more relevant than ever. Here, we consider the framework known as Controlled Query Evaluation (CQE), an innovative approach that safeguards confidentiality while still providing maximal query answers. We present an extension of this framework that enhances its expressivity through the use of rich forms of data protection rules. We explore the practical importance of these rules and some of the technical underpinnings that make this system effective. We then study some computational properties when data are managed through ontologies specified in DL-LiteR, a popular language designed for efficient reasoning in data-intensive applications.