Towards Normalized Systems from RDF with SPARQL

Frontiers in artificial intelligence and applications2022

Marek Suchánek, Herwig Mannaert, Robert Pergl

Abstract

Normalized Systems are a model-driven development technique focusing on evolvability and sustainability of resulting enterprise information systems. It applies well-defined principles to create a fine-grained modular structure while limiting combinatorial effects. The systems are generated (or, more precisely, expanded) from models of so-called NS Elements. NS has its own modelling language; however, interoperability with other knowledge representations is necessary. This work presents our solution for transforming knowledge kept in one of the most generic forms – RDF semantic triples – to NS Elements. The transformation enables mapping using RDFS/OWL ontologies describing both the input RDF. It utilizes SPARQL for executing the transformation to RDF based on the existing NS Element ontology. The presented transformation is demonstrated on an example case study, and its features and limitations are discussed together with potential future steps.

Related Papers

→ Overviewing the RDF(S) Semantic Web(2010)6 cited
→ An Object-Oriented Approach for Storing and Retrieving RDF/RDFS Documents(2007)5 cited
Viewing and Querying Topic Maps in terms of RDF(2008)
→ Toward Scalable Reasoning over Annotated RDF Data Using MapReduce(2012)2 cited
Knowledge Presentation Through RDF and its Application(2009)