– We are in the early stages of the “Kunnskapsgrafer Team” which will facilitate the use of knowledge graphs in the police. There will be a new team in the Knowledge delivery area, says system architect Lars.

He explained that all systems speak their own unique internal language.

– Comprehension of data naturally becomes problematic if everyone is communicating in a different language that no one else understands. Semantic graph technology allows systems to share data in the same language. A shared understanding of data across systems is key to breaking down data silos, and allows us to see new connections that allow us to create new knowledge.

Lars goes on to explain why the technology is so valuable.

– The reason why the big successful companies in the world use semantic technology is because they understand the value of seeing data in context. The value of data is enormous when it can be reused and viewed in the context of multiple data sets.

This will create new opportunities for us in policing sitting on large datasets segregated in different systems.

– When data is lifted up in a semantic knowledge graph, we can link the data together and ask new questions that were not possible before. In addition, we can validate data across systems and detect irregularities that we can investigate further. Knowledge graphing is a widely used technology to improve data quality and optimize it for reuse.

Drawn knowledge graph

All participants were tasked with drawing their domain knowledge about the real world as a knowledge graph. The knowledge graph is another way of modeling data in which we don’t force data into relational tables and databases, but instead let it flow in a natural way. Two of those who came to learn more about semantic technology were Amandeep and Heidi who work with data.

– I listened to a podcast about knowledge graphs a few weeks ago. It shows that to be data-driven, one has to start looking at knowledge graphs, said Amandeep.

– Connecting data is one of the most important things we do. We need to organize the data so that it has value, added Heidi.