The　advent　of　smart　manufacturing　in　Industry　4.0　signifies　the　arrival　of　the　era　of　connections.　As　an　excellent　communication　protocol,　Object　linking　and　embedding　for　Process　Control　Unified　Architecture　(OPC　UA)　can　address　most　semantic　heterogeneity　issues.　However,　its　semantics　are　not　formally　defined　at　the　application　layer.　To　address　the　information　silo　problem　caused　by　semantic　heterogeneity,　a　method　named　Querying　of　Ontology　Mapping-based　OPC　UA　(QOMOU)　is　proposed.　It　extracts　the　information　models　of　OPC　UA　servers　into　resource　description　framework　triples,　utilizes　web　ontology　language　for　semantic　enrichment　and　inference,　and　employs　a　semantic　similarity　model　for　event　ontology　mapping　to　improve　query　efficiency.　The　method＇s　effectiveness　is　validated　through　functional　queries　using　the　SPARQL　protocol　in　Apache　Jena.　The　query　efficiency　is　5%　higher　on　average　compared　to　both　structured　query　and　extensible　markup　languages.　Moreover,　by　employing　a　keyword-matching　algorithm,　the　query　accuracy　of　the　existing　heterogeneous　data　integration　scheme　is　improved　by　4%　on　average.　This　enhancement　can　boost　the　operational　efficiency　of　Internet　of　Things　systems　based　on　the　OPC　UA　architecture.　©　2024　IEEE.