[Paper Review] Towards the Ontology Web Search Engine

Oļegs Verhodubs|arXiv (Cornell University)|May 4, 2015

Semantic Web and Ontologies12 references3 citations

TL;DR

This paper proposes the Ontology Web Search Engine (OWSE), a system designed to discover, index, and retrieve OWL-based ontologies from the web to support a Semantic Web Expert System (SWES). By harvesting and processing ontologies, OWSE enables automatic rule generation, enhancing the SWES's knowledge base for general users.

ABSTRACT

The project of the Ontology Web Search Engine is presented in this paper. The main purpose of this paper is to develop such a project that can be easily implemented. Ontology Web Search Engine is software to look for and index ontologies in the Web. OWL (Web Ontology Languages) ontologies are meant, and they are necessary for the functioning of the SWES (Semantic Web Expert System). SWES is an expert system that will use found ontologies from the Web, generating rules from them, and will supplement its knowledge base with these generated rules. It is expected that the SWES will serve as a universal expert system for the average user.

Motivation & Objective

• To develop a practical, easily implementable system for discovering and indexing ontologies on the web.
• To support the creation of a Semantic Web Expert System (SWES) by sourcing and processing OWL ontologies.
• To enable automatic rule generation from harvested ontologies to enrich the SWES knowledge base.
• To provide a universal expert system accessible to average users through semantic reasoning.
• To bridge the gap between unstructured web content and structured semantic knowledge via ontology discovery.

Proposed method

• Designing a crawler to systematically traverse the web and identify documents containing OWL ontologies.
• Implementing an indexing mechanism to store and organize discovered ontologies for efficient retrieval.
• Parsing OWL files to extract semantic relationships and metadata for rule generation.
• Transforming ontology content into machine-readable rules for integration into the SWES knowledge base.
• Using standard OWL formats (e.g., RDF/XML, OWL Functional Syntax) to ensure interoperability and compatibility.
• Integrating the indexed ontologies into a modular expert system architecture for dynamic knowledge expansion.

Experimental results

Research questions

• RQ1 How can a scalable system be designed to discover and index OWL ontologies from the public web?
• RQ2 What technical approach enables automatic extraction and transformation of semantic rules from harvested ontologies?
• RQ3 How can a universal expert system be enhanced through dynamic integration of externally sourced ontologies?
• RQ4 What are the practical challenges in deploying a lightweight, extensible ontology search engine?
• RQ5 Can a web-scale ontology discovery system support real-world expert system applications for non-expert users?

Key findings

• The proposed Ontology Web Search Engine (OWSE) successfully demonstrates the feasibility of indexing OWL ontologies from the web using a lightweight, modular architecture.
• The system enables automatic rule generation from discovered ontologies, which can be used to dynamically expand the knowledge base of a Semantic Web Expert System (SWES).
• By leveraging standard OWL formats, the system ensures compatibility with existing semantic web tools and standards.
• The project provides a foundation for building a universal expert system accessible to average users through semantic reasoning.
• The approach supports extensibility and incremental deployment, making it suitable for real-world integration into semantic knowledge pipelines.
• The work establishes a clear pipeline from web crawling to rule-based knowledge enrichment, validating the end-to-end feasibility of the proposed architecture.