<i>POTS</i> - A Polyparadigmatic Ontology Term Search with Fine-Grained Context Steering using Hyper-Level Vector Spaces

We present a novel microservice-based system, that facilitates a polyparadigmatic ontology term search (leveraging semantic search via vector embeddings, keyword search, and attribute filters).The search index strategy intends to preserve important semantic aspects of the ontological context of a term (selected attributes and term relationships) using structured search fields and multilevel vector spaces assembling hyper-level vector spaces.The flexible, yet simple query API allows fine-grained search requests based on a combination of fuzzy and exact filters.The architecture is based on a highly automatable and flexible Docker Compose setup strategy.While deploying the system for a local ontology is only one command away, the setup also allows ingesting a configurable subset of over 1,800 published ontologies in over 12,000 versions via DBpedia Archivo.