PROV4ITDATA

Data portability enables users to control their data on the Web. Initiatives such as the Data Transfer Project take a step in this direction, providing an open-source, service-to-service data portability platform allowing individuals to move their data whenever they want.

However, such efforts — being hard-coded — miss transparency and interoperability. On the one hand, when data is transferred between services, there is no trust in whether this transfer was of high quality. Assessment requires reviewing the source code, as data provenance is unavailable. On the other hand, complying to this hard-coded platform requires development effort to create custom data models. Existing interoperability standards are neglected.

In this project, we propose an improved solution that is fully transparent and has fine-grained configuration to improve interoperability with other data models. To achieve this, we will exploit and advance the existing open-source tools RML.io and Comunica and show its extensibility by directly applying it to the Solid ecosystem. RML.io is a declarative and generic toolset to transparently generate Linked Data from (semi-)structured heterogeneous data with automatic data provenance and fine-grained configuration to extract and transform (parts of) the source data. Using Comunica, we can query multiple intermediate datasets to transfer to a new service, generating a provenance trail of where the resulting data came from.

We improve current data portability approaches by combining RML.io and Comunica for a fully transparent transfer process, where assessing the provenance trail can add trust. The transfer of personal data can be assessed before the data is accessed, and legal audits can be performed automatically based on the structured and semantically sound provenance trail. To show its applicability and extensibility for decentralized environments, we will connect it to the Solid ecosystem, giving users full control over their data.