Mining Hierarchies and Similarity Clusters from Value Set Repositories

A value set is a collection of permissible values used to describe a specific conceptual domain for a given purpose. By helping to establish a shared semantic understanding across use cases, these artifacts are important enablers of interoperability and data standardization. As the size of repositories cataloging these value sets expand, knowledge management challenges become more pronounced. Specifically, discovering value sets applicable to a given use case may be challenging in a large repository. In this study, we describe methods to extract implicit relationships between value sets, and utilize these relationships to overlay organizational structure onto value set repositories. We successfully extract two different structurings, hierarchy and clustering, and show how tooling can leverage these structures to enable more effective value set discovery.