Title: Taggle: Scalable Visualization of Tabular Data through Aggregation,
Abstract: Visualization of tabular data---for both presentation and exploration
purposes---is a well-researched area. Although effective visual presentations
of complex tables are supported by various plotting libraries, creating such
tables is a tedious process and requires scripting skills. In contrast,
interactive table visualizations that are designed for exploration purposes
either operate at the level of individual rows, where large parts of the table
are accessible only via scrolling, or provide a high-level overview that often
lacks context-preserving drill-down capabilities. In this work we present
Taggle, a novel visualization technique for exploring and presenting large and
complex tables that are composed of individual columns of categorical or
numerical data and homogeneous matrices. The key contribution of Taggle is the
hierarchical aggregation of data subsets, for which the user can also choose
suitable visual representations.The aggregation strategy is complemented by the
ability to sort hierarchically such that groups of items can be flexibly
defined by combining categorical stratifications and by rich data selection and
filtering capabilities. We demonstrate the usefulness of Taggle for interactive
analysis and presentation of complex genomics data for the purpose of drug
discovery.