The development of ICTs (Information and Communication Technologies) and the usage of personal data for both research and commercial purposes over the last years have brought the question of the protection of personal data. The GDPR (General Data Protection Regulation) has defined the ways how personal data should be treated, but the application of these requirements still remains an open issue.

Linked open data sources and the semantic web has become a precious data source for data analytics tasks and data integration. The growing data set sizes of RDF Knowledge Graph data need scalable processing and analytics techniques. The processing power of in-memory frameworks which can perform scalable distributed semantic analytics like SANSA, make use of Apache Spark and Apache Jena to provide start-to-end extensive scalable analytics on RDF knowledge graphs.

The last decades witnessed a significant evolution in terms of data generation, management, and maintenance, especially in the RDF format. Moreover, in the energy domain, semantic data is finding its way and can be used for various data

Ensuring the semantic interoperability issues between heterogeneous systems is very challenging task.  Using a common semantic data model, is a central element to ensure this semantic interoperability. In fact, a common semantic data model allows heterogenous systems to share the same meaning of entities that enables them to interoperate. Ontologies are recognized as the corner stone element to build a common semantic model.