Interactively using Semantic Web knowledge: Creating scalable abstractions with FacetOntology

The amount of knowledge accessible on the Semantic Web is growing, and there is a need for a scalable solution to facilitate exploring that data. Currently approaches to exploring Semantic Web data either focus on exploring resources individually, following links during exploration, and making little use of collated data, or take the approach of collating and aligning multiple sources into one store for one purpose, and hand-crafting a specific browsing interface onto it. We present an approach that provides a scalable browsing interface, which can browse knowledge from the Semantic Web at will. Our approach creates abstractions of knowledge, collated into facets, which are described using FacetOntology. FacetOntology facilitates descibing facets from RDF data, suitable for use in creating datasets for faceted browsing.

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