Faceted browsing is a widely spread, intuitive, and interactive search paradigm for information collections based on the metadata of its items. However, it has the problem that every selected criterion is mandatory so that less important ones may reduce the result set and interesting items may be removed unintentionally. On the other hand, choosing only very few facets yields to an unmanageable set of items wherein the best ones do not become obvious. In this paper, we propose weighted faceted browsing, which seamlessly extends the existing faceted browsing paradigm. Besides basic filtering capabilities, it provides a sophisticated relevance ranking of the result set based on the distinction between mandatory and weighted optional search criteria. Further, we show its practicability within an information visualization workbench to facilitate the end user's search for visualization components based on their characteristics.
Interactive visual analytic systems can help to solve the problem of identifying relevant information in the growing amount of data. For guiding the user through visualization tasks, these semi-automatic systems need to store and use knowledge of this interdisciplinary domain. Unfortunately, visualisation knowledge stored in one system cannot easily be reused in another due to a lack of shared formal models. In order to approach this problem, we introduce a visualization ontology (VISO) that formally models visualization-specific concepts and facts. Furthermore, we give first examples of the ontology's use within two systems and highlight how the community can get involved in extending and improving it.
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