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