The main goal of this Thesis is to find ways to help users of Web services deal with this overload, offering services that match their preferences and respect their rights, aiding them in taking control over the publication and sharing of their personal data.

In this context, the use and extension of data protection vocabularies and machine-readable policy languages are suitable for the representation of individual privacy preferences and requirements, fine-grained policies for the processing of personal data and other machine-readable information related to GDPR rights and obligations, including the logging of processing activities for future auditing and the exercising of user's personal data-related rights. Furthermore, these specifications can also be used to establish a policy matching mechanism where fine-grained GDPR-aligned access control policies are used to manage and determine access to decentralised personal datastores, such as Solid Pods. Solid is a decentralised data environment that detaches the storage of data from the processing of said data performed by data-driven applications. Such an architecture allows Web users to have better control over the movement of their personal data and regain trust in the services using it as the users are the ones specifying who can access their data. The policy matching algorithm and the developed vocabularies are also used to deal with the requirements of sharing health data and to manage the requirements of the newly enforced Data Governance Act to showcase the representational capabilities of the developed technologies to cover specific use cases and to be expanded to deal with new demands, in particular, related to the expression of data reuse policies and consent terms.