Publication details

Taggle: Combining Overview and Details in Tabular Data Visualizations


FURMANOVÁ Katarína GRATZL Samuel STITZ Holger ZICHNER Thomas JAREŠOVÁ Miroslava LEX Alexander STREIT Marc

Year of publication 2020
Type Article in Periodical
Magazine / Source Information Visualization
MU Faculty or unit

Faculty of Informatics

Keywords visualization; tabular data
Description 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 by a case study conducted by a domain expert on complex genomics data analysis for the purpose of drug discovery.

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