Master theses

Synchronized Knowledge

Keywords: Linked Data, Digital Twins, Knowledge Graphs, Provenance

Promotors: Ben De Meester

Students: max 2


Knowledge lives in graphs. Knowledge graphs are the technology to interlink data across existing systems and derive new knowledge. It's what the Google Knowledge Graph is built on, it's what drives Zalando, IKEA, etc.

However, knowledge is dynamic. Things change all the time, but currently, your knowledge graph is a static representation and changes to the knowledge graph aren't fed back to your source system. By using a (standardized) mapping system to map existing data into a knowledge graph, we have the opportunity to use that mapping bidirectionally: not only map existing source data to a target knowledge graph, but use the same configuration to map changes in the target knowledge graph back to the source data.

This will bring the best of both worlds: performant existing systems, insightful knowledge graphs, and a full synchronization system between the two.


Devise and implement a system that uses the RML mapping language to map between a data source system and a knowledge graph. The result is a demonstrator where changes ripple back to the source.