Facetlens : Exposing Trends And Relationships To Support Sensemaking Within Faceted Datasets / quote 1 of 4
Linear facets and pivoting between facets
FacetLens extends previous faceted systems in two ways. First, in addition to more traditional facet types such as single-value, multi-value, and hierarchical, FacetLens implements linear facets. While attribute values are intrinsically categorical, linear facets permit the visual representation of order within a facet in a way that allows data trends such as temporal relationships to be pre-served and exposed. Second, it provides users with the ability to pivot between related facets at any point during the exploration. This is important because it allows users to maintain a sense of context while they quickly and efficiently explore various areas within the dataset