We align three upper ontologies that sit under UK and NATO defence data infrastructure: the Information Exchange Standard (IES), the Higher Quality Data Model (HQDM) that underpins the National Digita...
arXiv:2608. 05867v1 Announce Type: new Abstract: The use of ontologies and knowledge graphs is becoming increasingly widespread in the defence and national security domain.
The use of ontologies and knowledge graphs is becoming increasingly widespread in the defence and national security domain. Numerous ontologies have been developed through initiatives led by academia, industry, and government.
arXiv:2608. 08122v1 Announce Type: new Abstract: In this paper we discuss the foundations behind a novel methodology for the validation of semantic mappings between different data sources based upon different foundation ontologies, where the methodology builds a framework based upon the metaphysical commitments of the ontologies.
arXiv:2607. 29553v1 Announce Type: new Abstract: Organizations increasingly define operational metrics in structured, machine-readable formats to monitor systems, processes, and compliance.
arXiv:2506. 01232v2 Announce Type: replace-cross Abstract: Deriving OWL ontologies from relational database schemas supports semantic interoperability and downstream tasks such as knowledge graph population, ontology-based data access, graph-based learning, and automated reasoning.
arXiv:2607. 24551v1 Announce Type: new Abstract: Maintenance regulations are complex legal texts that are difficult to exploit when addressing a specific case and challenging to integrate into operational systems.
arXiv:2608. 10644v1 Announce Type: new Abstract: Extraction produces candidate entities and relationships; writing them into a graph is where identity is decided, and identity decisions are destructive in a way extraction errors are not.
arXiv:2607. 27130v1 Announce Type: new Abstract: Ontology matching (OM) has traditionally been formulated as either equivalence discovery or subsumption matching.
The paper introduces the European Crisis Management Ontology (ECMO), an OWL-based modular ontology designed to serve as a cross‑sectoral reference for disaster risk reduction and response. ECMO-CORE contains core crisis management concepts such as hazard, event, exposure, impact, and response measure, employing ontology design patterns and OWL2 punning to clarify ambiguities. Domain‑specific modules, including a public health module aligned with SNOMED CT and ICD‑11, extend the ontology; a demonstration shows ECMO can transform unstructured epidemiological news into a compliant knowledge graph, illustrating its potential for consistent knowledge integration.
UniDataAgent (UniDataAgent) is an ontology‑grounded system designed to automate enterprise question‑to‑report tasks while preserving organization‑specific semantics. It separates semantic acquisition from online execution, with an Ontology Acquisition and Validation (OAV) stage that builds versioned ontologies from metadata, business knowledge, and expert input, and a Question‑to‑Report Execution (QRE) stage that retrieves semantic contracts, coordinates skills and data tools, validates results, and produces evidence‑linked reports. In a deployment across 27 enterprise tables and thousands of metric types, ontology construction took a few hours versus a week manually, and report generation took minutes versus several working days, achieving 95.0% strict accuracy on real business questions compared to 72.5% for document RAG.
arXiv:2608.21418v1 Announce Type: new Abstract: Manufacturing knowledge graphs that integrate data from heterogeneous industrial systems face a trust deficit: consumers cannot determine whether queri...