Abstract
The healthcare sector faces multiple challenges in implementing, maintaining and upgrading its systems, including technical, security and interoperability difficulties. Ontologies are the key to achieve and improve healthcare interoperability, in the form of a permanent artefact of the specification of each of the medical concepts. However, since different ontologies may have contradicting or overlapping parts, the need for the creation of ontology matching techniques for identifying similarities between them is rising. In the meantime, a large number of ontologies, vocabularies and taxonomies, as well as medical standards are constructed and globally adopted (e.g. HL7 FHIR), without promising the existence of a single global ontology, any time soon. Thus, a substantial overhaul of methodology is required to address the real complexity of health. This can be achieved through the FHIR Ontology Mapper (FOM) technique that is presented in this paper, which aims at constructing healthcare ontologies from any data source, and then identifying both the structural and semantic similarities between the latter and the HL7 FHIR resources ontologies. The final matchings derive from the mean of the latter, aiming at translating healthcare data of any type, into the widely adopted HL7 FHIR standard, thus enabling interoperability and improving the quality of patient care and research