The goal of this work is to put into context recent updates in ontology engineering and present the necessary additional information targeted to reuse by providing an updated overview and proposing a two-tier categorisation, believed to be the first review to offer such an intra-category classification.
The results suggest that OntoExtend is useful as a drafting assistant for requirement-driven ontology extension in real world scenarios, while remaining sensitive to CQ specificity and modelling profile.
Anna Sofia Lippolis, Mohammad Javad Saeedizade, Stefan Schmid et al.· 1 citation
The Semantic Web enables data exchange and knowledge exploitation through SPARQL queries; however, users often encounter difficulties when formulating such queries, leading to unexpected results and iterative trial-and-error processes. These issues are aggravated by incomplete knowledge of the application domain and the underlying ontological schema, frequently causing unnecessary query executions and increased computational load on RDF repositories. This work proposes a method for the prior syntactic and semantic validation of SPARQL queries, based on an ontology and independent of its instances. The method operates before query execution and detects inconsistencies arising from literal writing errors and violations of object property axioms, providing explicit feedback to users. The development of the proposed approach follows a classical methodological framework grounded in the software engineering process. Experimental results show that the additional computational overhead introduced by validation is minimal, while the benefits are significant in scenarios involving incorrect queries. In particular, prior validation prevents the execution of erroneous queries, reduces processing time, and maintains negligible overhead for correct queries, demonstrating a favorable trade-off between computational efficiency and reduced manual intervention. Overall, the results indicate that prior validation improves SPARQL query quality and enhances developer productivity in semantic data–driven applications.
Juan COLLIO BARRA, A. Aguilera, Irvin Dongo· CLEI Electronic Journal· 0 citations
Domain-specific information systems often maintain their data model, rule base, and application infrastructure as separate artifacts, complicating maintenance and pre-deployment verification. This study investigates whether these artifacts can be unified in a verifiable ontology-to-code pipeline without changing the expected classifications. The proposed Model-Driven Architecture uses the Business Application Builder framework and a Web Ontology Language 2 Description Logic ontology to represent domain structure, classification rules, and generation metadata. HermiT verifies consistency, satisfiability, and subsumption under open-world semantics before code generation. The generator produces persistence, business-logic, data-transfer, and presentation layers, while the generated Java application evaluates stored records under closed-world semantics and resolves overlapping categories using ontology-declared priorities. In a Serbian research-evaluation case study, the generated system reproduced the M30 and M33 classifications of an established Jess implementation. An internal secondary experiment generated and executed a prenatal-diagnosis application; all six runtime classifications matched the HermiT entailments and expected outcomes. The public artifact independently reproduces the ontology-level experiments but excludes the proprietary generator and generated source code. The results support the feasibility of ontology-driven generation for static-classification systems, whereas arithmetic risk computation and temporal event processing remain better suited to complementary procedural technologies. No performance superiority is claimed.
Borivoj Bogdanović, S. Nikolić· Computers· 0 citations