Unpacking the Semantic Web: Integrated Insights into Ontologies, Linked Data Applications, and Open Data Transformation (2009-2025)

This wrap-up paper synthesizes findings from a collection of my research works from 2009 to 2025 exploring the multifaceted landscape of Semantic Web (SW) technologies, artifacts, methods, and tools. More specifically, by examining the role and application of ontologies in various domains including business models, predictive maintenance, and manufacturing, the cohabitation and conversion between relational databases and ontologies, techniques for natural language to SPARQL query translation, and the exploitation of Linked Data for sample web applications, as well as approaches for transforming Open Government Data (OGD) into Linked Open Data (LOD) to exploit its potential fully, this paper identifies key trends, limitations, and potential synergies. Through a deep analysis of existing methodologies and frameworks, we aim to provide new insights into the integrated application of these technologies to enhance data interoperability, knowledge representation, and intelligent information retrieval, ultimately contributing to the evolution of the Semantic Web. We propose a classification of crucial covered domains in the semantic web context, highlighting each work's contributions, challenges, and limitations, as well as a framework for delimiting the dimensions of these studies. Additionally, we outline KPIs to enhance the practicability and adoption of semantic web technologies, artifacts, methods, and tools. This paper has been written with the assistance of notebookLM and Quillbot to summarize the paper's content.