We have witnessed about a decade’s effort in opening up government institutions around the world by making data about their services, performance and programmes publicly available on open data portals. While these efforts have yielded some economic and social value particularly in the context of city data ecosystems, there is a general acknowledgment that the promises of open data are far from being realised. A major barrier to better exploitation of open data is the difficulty in finding datasets of interests and those of high value on data portals. This article describes how the implicit relatedness and value of datasets can be revealed by generating a knowledge graph over data catalogues. Specifically, we generate a knowledge graph based on a self-organizing map (SOM) constructed from an open data catalogue. Following this, we show how the generated knowledge graph enables value characterisation based on sociometric profiles of the datasets as well as dataset recommendation.