  Knowledge Graphs (KGs) have proven to be a reliable way of structuring data.
They can provide a rich source of contextual information about cultural
heritage collections. However, cultural heritage KGs are far from being
complete. They are often missing important attributes such as geographical
location, especially for sculptures and mobile or indoor entities such as
paintings. In this paper, we first present a framework for ingesting knowledge
about tangible cultural heritage entities from various data sources and their
connected multi-hop knowledge into a geolocalized KG. Secondly, we propose a
multi-view learning model for estimating the relative distance between a given
pair of cultural heritage entities, based on the geographical as well as the
knowledge connections of the entities.
