One of the ongoing challenges for effective utilization of heritage science data is the lack of access to well-organized and accessible extant data sets and the need to structure data in formats that allow interrogation and integration of related data. This need for data fusion expands to both subjective and objective measurements and descriptors, as well as a long-overdue need for established guidelines for metadata and shared terminologies, or more critically, ontologies. Research into this area has shown the need for Knowledge Organization Systems (KOS) that bridge and integrate multiple ontologies that address specific needs – for example the Getty Vocabularies for cultural heritage terms, the Linked Art model for a simplified core CIDOC-CRM, as well as the OBO Foundry and other scientific ontologies for measurements and heritage science terminology.[1]