Taggle: Combining overview and details in tabular data visualizations. (April 2020)

• Record Type: Journal Article
• Authors: Furmanova, Katarina; Gratzl, Samuel; Stitz, Holger; Zichner, Thomas; Jaresova, Miroslava; Lex, Alexander; Streit, Marc
• Is Part Of: Information visualization. Volume 19:Number 2(2020)
• Page Start: 114
• Page End: 136
• Publication Date: 2020-04
• Subjects: Visualization techniques -- tabular data -- multidimensional data visualization -- aggregation -- hierarchical grouping and sorting -- degree of interest -- focus and context; Information visualization -- Periodicals; 006.605
• DOI: 10.1177/1473871619878085
• Languages: English
• ISSNs: 1473-8716

Abstract

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.