Industry 2: Deploying Enterprise Level, Ontology-Driven Faceted Search

author: Ralph Hodgson, Top Quadrant
published: Feb. 25, 2007,   recorded: November 2006,   views: 5269

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Currently, one of the most practical application spaces for Semantic Web technologies is creating an ontological layer over existing legacy databases. Such layering allows flexible applications to be built without the cost of restructuring large amounts of data while maintaining the performance advantages of a relational database. Whereas applications designed to directly query a database encode business logic in specific queries, ontological layer offers a flexible framework whereby dynamically generated queries are resilient to schema changes. This same approach can be used to query multiple decentralized databases from a seemingly centralized point of view, allowing access to multiple database schemas via a single interface. In an ontology, Semantic Web technologies such as RDFS, OWL and SWRL can be used to specify composition rules and abstractions, making it possible to answer complex questions without developing complex queries. TopQuadrant has applied this approach to develop and deploy a flexible faceted search system over a network of large, decentralized legacy databases. The system uses ontologies in two distinct ways: as an abstraction layer over an underlying relational data model; and as a search interface model driving the system itself. This model-based approach allows dynamic system configuration simply through changes to the model. The model controls what data can be searched, what facets can be used for building queries, and even how data should be displayed. The system combines the structured power of ontologies with more conventional keyword-based search over a related unstructured document corpus. The resulting hybrid system provides capabilities beyond what is possible with either approach alone. This talk will describe the process used for developing the ontological layer; discuss challenges and technical solutions in integrating the databases and bringing together structured and unstructured search. We will also show the benefits of using ontology to specify the search interface and interaction.

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