Ontology-based Queries over Cancer Data

TL;DR

This paper introduces an ontology-based query system for cancer data that enhances data access by translating high-level domain queries into infrastructure-specific queries using reasoning, improving semantic data integration.

Contribution

It presents a novel approach to generate OWL2 ontologies from data metadata and a reasoning-based query rewriting process for better data retrieval in biomedical infrastructures.

Findings

Improved query translation accuracy

Enhanced data integration capabilities

Performance evaluation demonstrates efficiency

Abstract

The ever-increasing amount of data in biomedical research, and in cancer research in particular, needs to be managed to support efficient data access, exchange and integration. Existing software infrastructures, such caGrid, support access to distributed information annotated with a domain ontology. However, caGrid's current querying functionality depends on the structure of individual data resources without exploiting the semantic annotations. In this paper, we present the design and development of an ontology-based querying functionality that consists of: the generation of OWL2 ontologies from the underlying data resources metadata and a query rewriting and translation process based on reasoning, which converts a query at the domain ontology level into queries at the software infrastructure level. We present a detailed analysis of our approach as well as an extensive performance evaluation. While the implementation and evaluation was performed for the caGrid infrastructure, the approach could be applicable to other model and metadata-driven environments for data sharing.