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Updated: Sep 11, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Published on: June 13, 2025

An ontology-driven knowledge graph for tourism information management.

Subhashis DAS¹, Mayukh Bagchi²

¹Department of Computer Science and Automation, Universidad de Salamanca, Salamanca, Castile and León, 37007, Spain.

Open Research Europe

|August 12, 2025

Summary

This summary is machine-generated.

This study introduces ontology-driven Knowledge Graphs, powered by Artificial Intelligence (AI), to address complex tourist information needs. This AI approach enhances tourism data services for intricate user queries.

Keywords:

Conceptual Disentanglement Faceted Ontology Knowledge Graph Ontology Modelling Tourism Tourism and Artificial intelligence (AI)

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Area of Science:

Artificial Intelligence
Knowledge Representation
Information Science

Background:

Modern tourism generates complex user queries, ranging from simple to highly specific.
Existing Information and Communications Technology (ICT) infrastructures struggle to meet the demand for fine-grained tourism data.
Cultural, linguistic, and economic diversity complicates information provision for tourists.

Purpose of the Study:

To propose and advocate for ontology-driven Knowledge Graphs as a solution for advanced tourism information services.
To provide a methodology for developing AI-backed systems capable of handling complex tourist queries at scale.
To enhance the granularity and accessibility of tourism data.

Main Methods:

Development of a theoretically and implementationally sound methodology.
Leveraging Artificial Intelligence (AI) for data processing and service provision.
Utilizing ontology-driven Knowledge Graphs for structured data representation.

Main Results:

A comprehensive tourism-specific ontology-driven knowledge graph was developed.
The knowledge graph contains 4264 Resource Description Framework (RDF) statements.
The developed system is validated and ready for integration and extension.

Conclusions:

Ontology-driven Knowledge Graphs offer a robust solution for complex tourism information needs.
The proposed AI methodology effectively addresses the limitations of current ICT in tourism.
The developed knowledge graph is reusable, extensible, and exploitable within the tourism sector.