Approach to developing a cluster ontology

A conceptual approach to developing an ontology for the "Clusters" subject area and forming corresponding development tools is presented. The cluster ontology is fundamental for addressing cluster policy issues using artificial intelligence technologies. The study focuses on the hierarchy of concepts in the "Clusters" ontology and the structure of relations between them. The objectives are to formalize the taxonomic hierarchy of the "Clusters" ontology and determine the types and structure of relationships between ontology elements. The study utilized a set of information technologies unified by a single semantic framework: the ontological language OWL, the Protege ontology editor for building knowledge bases, and software tools for working with ontologies. The classification criteria and types of semantic networks in the "Clusters" subject area are examined. The types of relations applicable in constructing a semantic network for this subject area are identified. New types of clusters, such as "Innovation multicluster" and "Innovation hypercluster," are introduced. For the first time, the structure of the taxonomic hierarchy of the "Clusters" ontology is proposed, and the main types of relationships between elements are identified. The directions for applying the proposed ontology for the digitalization of regional management systems are outlined.