The importance and relevance of terminology and ontology are increasing in this age of digitalization and automation. Even though terminology and ontology are considered separate disciplines, there are synergies between the two disciplines. This becomes apparent when the ontological processes and an ontology are examined for existing or missing terminological influences.
There are far more connections between terminology and ontologies than one would have imagined. For instance, the respective main components of terminology and ontology correspond to each other. Classes, instances, and properties in ontologies are the respective counterparts of superordinate concepts, subordinate concepts, and terminology relations. A more in-depth examination of the structure reveals many more corresponding elements. In this regard, the formal representation of ontologies is a perfect example as it entails many elements, which can also be found in terminology databases.
An exciting aspect emerges when a comparison of the processes in terminology and ontology management is made. When defining the domain, concepts/classes, subordinate concepts/instances, and relations/properties, the processes are similar in the first half. Nevertheless, as soon as the management, control, and maintenance aspects of the defined terminology begin, the ontology process seems to be over. This indicates that high-quality ontologies should be based on an already standardized cleansed and continuously maintained terminology.
There are also deviations and errors, mostly arising from this very lack of terminological control and influence. To conclude, efficient terminology management, including consistent terminology and control, is indispensable for many critical business areas. Efficient terminology management is also essential for creating and modeling ontologies because ontologies reuse the terminology defined and maintained during terminology management. Additionally, ontologies enrich it with semantic information to make it machine-readable and usable in the Semantic Web.
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