We developed a novel analytical environment to aid in the examination of the extensive amount of interconnected data available for genome projects. Our focus is to enable flexibility and abstraction from implementation details, while retaining the expressivity required for post-genomic research. To achieve this goal, we associated genomics data to ontologies and implemented a query formulation and execution environment with added visualization capabilities. We use ontology schemas to guide the user through the process of building complex queries in a flexible Web interface. Queries are serialized in SPARQL and sent to servers via Ajax. A component for visualization of the results allows researchers to explore result sets in multiple perspectives to suit different analytical needs. We show a use case of semantic computing with real world data. We demonstrate facilitated access to information through expressive queries in a flexible and friendly user interface. Our system scores 90.54% in a user satisfaction evaluation with 30 subjects. In comparison with traditional genome databases, preliminary evaluation indicates a reduction of the amount of user interaction required to answer the provided sample queries.
Mendes, P. N.,
Sheth, A. P.,
& Kissinger, J. C.
(2008). TcruziKB: Enabling Complex Queries for Genomic Data Exploration. Proceedings of the IEEE International Conference on Semantic Computing, 432-439.