  Most tabular data visualization techniques focus on overviews, yet many
practical analysis tasks are concerned with investigating individual items of
interest. At the same time, relating an item to the rest of a potentially large
table is important. In this work we present Taggle, a tabular visualization
technique for exploring and presenting large and complex tables. Taggle takes
an item-centric, spreadsheet-like approach, visualizing each row in the source
data individually using visual encodings for the cells. At the same time,
Taggle introduces data-driven aggregation of data subsets. The aggregation
strategy is complemented by interaction methods tailored to answer specific
analysis questions, such as sorting based on multiple columns and rich data
selection and filtering capabilities. We demonstrate Taggle using a case study
conducted by a domain expert on complex genomics data analysis for the purpose
of drug discovery.
