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There is a plethora of datasets in various formats which are usually storedin files, hosted in catalogs, or accessed through SPARQL endpoints. In mostcases, these datasets cannot be straightforwardly explored by end users, forsatisfying recall-oriented information needs. To fill this gap, in this paperwe present the design and implementation of Facetize, an editor that allowsusers to transform (in an interactive manner) datasets, either static (i.e.stored in files), or dynamic (i.e. being the results of SPARQL queries), todatasets that can be directly explored effectively by themselves or otherusers. The latter (exploration) is achieved through the familiar interactionparadigm of Faceted Search (and Preference-enriched Faceted Search).Specifically in this paper we describe the requirements, we introduce therequired set of transformations, and then we detail the functionality and theimplementation of the editor Facetize that realizes these transformations. Thesupported operations cover a wide range of tasks (selection, visibility,deletions, edits, definition of hierarchies, intervals, derived attributes, andothers) and Facetize enables the user to carry them out in a user-friendly andguided manner, without presupposing any technical background (regarding datarepresentation or query languages). Finally we present the results of anevaluation with users. To the best of your knowledge, this is the first editorfor this kind of tasks.

Facetize: An Interactive Tool for Cleaning and Transforming Datasets for Facilitating Exploratory Search