WiseOWL: A Methodology for Evaluating Ontological Descriptiveness and Semantic Correctness for Ontology Reuse and Ontology Recommendations
Summary: arXiv:2604.12025v1 Announce Type: new
Abstract: The Semantic Web standardizes concept meaning for humans and machines, enabling machine-operable content and consistent interpretation that improves advanced analytics. Reusing ontologies speeds development and enforces consistency, yet selecting the optimal choice is challenging because authors lack systematic selection criteria and often rely on intuition that is difficult to justify, limiting reuse. To solve this, WiseOWL is proposed, a methodology with scoring and guidance to select ontologies for reuse.
Overview of WiseOWL Methodology
WiseOWL introduces a comprehensive methodology designed to enhance the process of selecting ontologies for reuse. It implements a scoring system based on four key metrics:
- Well-Described: This metric measures the documentation coverage of the ontology, assessing how thoroughly the concepts and relationships are defined.
- Well-Defined: Utilizing state-of-the-art embeddings, this metric evaluates the alignment between ontology labels and their definitions, ensuring clarity and precision.
- Connection: This metric captures the structural interconnectedness of the ontology, which is crucial for understanding how different concepts relate to one another.
- Hierarchical Breadth: This metric reflects the hierarchical balance of the ontology, indicating how well concepts are organized within a taxonomy.
Functionality and Implementation
WiseOWL outputs normalized scores ranging from 0 to 10 for each metric, accompanied by actionable feedback that guides users in their selection process. The methodology has been implemented as a user-friendly Streamlit application, which allows users to:
- Ingest OWL format ontologies.
- Convert ontologies to RDF Turtle format for compatibility.
- Access interactive visualizations that enhance understanding of the ontological structure and scoring results.
Evaluation and Results
The practical effectiveness of WiseOWL has been evaluated across six distinct ontologies, including:
- Plant Ontology (PO)
- Gene Ontology (GO)
- Semanticscience Integrated Ontology (SIO)
- Food Ontology (FoodON)
- Dublin Core (DC)
- GoodRelations
Initial results indicate that WiseOWL provides a promising framework for ontology selection, enabling users to make informed decisions that enhance both the quality and consistency of semantic data. By overcoming the limitations of intuition-based selection methods, WiseOWL aims to facilitate broader ontology reuse across various domains.
Conclusion
WiseOWL represents a significant advancement in the field of ontology management, providing a systematic approach to evaluating and selecting ontologies for reuse. As the Semantic Web continues to evolve, methodologies like WiseOWL will play a crucial role in ensuring that ontological resources are utilized effectively, thereby enhancing the overall quality of data interoperability and analytics in diverse applications.