Facetlens : Exposing Trends And Relationships To Support Sensemaking Within Faceted Datasets / quote 3 of 4
Linear facets expose trends over time
One set of interesting insights that can be made about a large collection of data such as a conference publication dataset involves meaningful trends. For example, which topics have come and gone in a conference? What is the publication trend of an author or an institute? What is the citation pattern of an author or a paper? Unfortunately, since the focus of most faceted systems is on presenting categorical selections, many systems also end up removing important visual ordering information. Facets are treated as lists of labels on subsets of the data, and so are attribute values within the facets.
FacetLens introduces the linear facet in which attribute values are visually presented in an explicit order, such as time. This permits exposing rich relationships between attribute values within a facet. Within the interface, linear facets are displayed horizontally across the bottom of the Facet area.