Highlights What are the main findings? We have developed an integrated and automated
methodology that leverages a pre-trained Large Language Model (LLM) to generate …

Resource Description Framework (RDF) can seen as a solution in today's landscape of
knowledge representation research. An RDF language has symmetrical features because …

Digital revolution produces massive, heterogeneous and isolated data. These latter remain
underutilized, unsuitable for integrated querying and knowledge discovering. Hence the …

This research presents a comprehensive methodology for utilizing an ontology-driven
structured prompts system in interplay with ChatGPT, a widely used large language model …

A critical issue in Big Data management is to address the variety of data–data are produced
by disparate sources, presented in various formats, and hence inherently involves multiple …

In this paper, we introduce three new implementations of non-native methods for storing
RDF data. These methods named RDFSPO, RDFPC and RDFVP, are based respectively on …

Offshore decommissioning represents significant business opportunities for oil and gas
service companies. However, for owners of offshore assets and regulators, it is a liability …

Hyper-graphs offer the opportunity to formulate logical statements about their components,
for example, using Horn clauses. Several models of Information Systems can be …

Open educational resources are currently becoming increasingly available from a multitude
of sources and are consequently annotated in many diverse ways. Interoperability concerns …

RDF and Property Graphs are data models that are being used to represent Knowledge
Graphs. The definition of methods to transform RDF data into Property graph data is …