The Massive Problem of Remote Changes in Ontology Reuse

Reusing existing datasets is a common practice in the Semantic Web, and it is also highly encouraged. Previous work on linking datasets has introduced and analysed different ways of linking but has failed to discuss the meaning and intentions behind the reuse of entities. This problem is aggravated by the fact Knowledge Graphs (KGs) and ontologies change over time. Currently, we lack an analysis of what impact the asymmetric evolution of the reused KGs has. Therefore, in this short paper, we evaluate how severe the problem of impacting remote changes is in practice by analysing the evolution of real-world ontologies. To this end, we collect a large corpus of open biomedical ontologies (759 ontologies) and provide statistics on their evolution, reuse (46.65%) and impacting changes (33.38%). We find that these KGs experience enormous amounts of impacting term reuse (7.59%), and the extent of the problem has been overlooked on a massive scale.