An increasing amount of organisations publish information as Linked Open Data (LOD). These data sets are semantically interconnected which we call the LOD Cloud. It is up to the publisher to choose which vocabularies and schemas are used to annotate the data, or even create new ones. This choice is not trivial and requires a detailed overview of various quality aspects for the available options, like the semantic expressiveness of the various logical variants, the popularity of the vocabularies and the interconnectedness with other data sets.
Digging into the Knowledge Graph (DiKG) is a project where we investigate these quality aspects for the vocabularies and schemas in the LOD. DiKG is a collaboration between DANS, the VU Amsterdam, the university of Wisconsin, U.S., the university of Alberta, CA, and the São Paulo State University, Brazil.