ONTOLOGICAL MODELING OF WEB APPLICATION STRUCTURE

Abstract

This article delves into the application of the ontological approach in modeling the structural components of web applications, emphasizing the design and implementation of a multi-level ontological model. As a case study, an online store was chosen to illustrate the capabilities of this method. The model comprises foundational classes — including Furniture, Customer, Price, Style, and others — each of which is further refined through hierarchically organized subclasses to reflect the complexity and diversity of real-world entities. This structure enables a more nuanced representation of domain knowledge, essential for building adaptive and scalable web systems.

To formalize relationships among these elements, a comprehensive set of object properties was introduced, describing various types of interactions and associations. Additionally, datatype properties were used to specify attributes such as numerical values, textual descriptions, and stylistic parameters. These components were synthesized into an ontological graph using standard semantic web technologies, ensuring logical consistency, transparency, and extensibility. This graph-based representation serves not only as a knowledge repository but also as a foundation for semantic queries and automated reasoning.

SPARQL, a powerful query language for RDF-based data, was employed to retrieve, filter, and manipulate ontological data efficiently. Through SPARQL queries, relationships between products, customer preferences, pricing models, and stylistic categories were extracted and analyzed. This enabled the creation of structured data sets suitable for visualization, recommendation systems, and performance evaluation. The model’s utility was validated through simulations of online store transactions, showcasing its ability to reflect realistic scenarios and decision-making processes.

Furthermore, the ontological framework was designed with adaptability in mind, allowing it to be reused and reconfigured for various application domains such as healthcare, education, or logistics. The study also addressed key challenges related to knowledge representation, including automation of ontology generation, graphical visualization of ontological graphs, and the streamlining of data processing workflows.

Overall, this research highlights the practical advantages of ontological modeling in web development. It supports data integration, semantic interoperability, and intelligent decision-making within complex information systems. The proposed methodology not only enhances conceptual clarity but also enables more efficient system evolution and maintenance. It provides a robust foundation for further research and development in the field of semantic technologies and intelligent web applications.