FURMANOVÁ, Katarína, Samuel GRATZL, Holger STITZ, Thomas ZICHNER, Miroslava JAREŠOVÁ, Alexander LEX and Marc STREIT. Taggle: Combining Overview and Details in Tabular Data Visualizations. Information Visualization. 2020, vol. 19, No 2, p. 114-136. ISSN 1473-8716. Available from: https://dx.doi.org/10.1177/1473871619878085.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Taggle: Combining Overview and Details in Tabular Data Visualizations
Authors FURMANOVÁ, Katarína (703 Slovakia, belonging to the institution), Samuel GRATZL, Holger STITZ, Thomas ZICHNER, Miroslava JAREŠOVÁ (203 Czech Republic, belonging to the institution), Alexander LEX and Marc STREIT.
Edition Information Visualization, 2020, 1473-8716.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10200 1.2 Computer and information sciences
Country of publisher United Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 0.956
RIV identification code RIV/00216224:14330/20:00115101
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1177/1473871619878085
UT WoS 000501443500001
Keywords in English visualization; tabular data
Tags International impact, Reviewed
Changed by Changed by: RNDr. Katarína Furmanová, Ph.D., učo 374538. Changed: 22/4/2021 19:14.
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.
PrintDisplayed: 23/7/2024 06:25