DocumentCode
21286
Title
Domino: Extracting, Comparing, and Manipulating Subsets Across Multiple Tabular Datasets
Author
Gratzl, Samuel ; Gehlenborg, Nils ; Lex, Alexander ; Pfister, Hanspeter ; Streit, Marc
Author_Institution
Johannes Kepler Univ. Linz, Linz, Austria
Volume
20
Issue
12
fYear
2014
fDate
Dec. 31 2014
Firstpage
2023
Lastpage
2032
Abstract
Answering questions about complex issues often requires analysts to take into account information contained in multiple interconnected datasets. A common strategy in analyzing and visualizing large and heterogeneous data is dividing it into meaningful subsets. Interesting subsets can then be selected and the associated data and the relationships between the subsets visualized. However, neither the extraction and manipulation nor the comparison of subsets is well supported by state-of-the-art techniques. In this paper we present Domino, a novel multiform visualization technique for effectively representing subsets and the relationships between them. By providing comprehensive tools to arrange, combine, and extract subsets, Domino allows users to create both common visualization techniques and advanced visualizations tailored to specific use cases. In addition to the novel technique, we present an implementation that enables analysts to manage the wide range of options that our approach offers. Innovative interactive features such as placeholders and live previews support rapid creation of complex analysis setups. We introduce the technique and the implementation using a simple example and demonstrate scalability and effectiveness in a use case from the field of cancer genomics.
Keywords
cancer; data visualisation; distributed databases; genomics; interactive systems; set theory; Domino; cancer genomics; complex analysis setups; heterogeneous data visualization; innovative interactive features; interconnected datasets; multiform visualization technique; multiple tabular datasets; subset comparison; subset extraction; subset manipulation; subset visualization; Biomedical measurements; Cancer; Data visualization; Genomics; Multiple coordinated views; categorical data; heterogeneous data; relationships; visual linking;
fLanguage
English
Journal_Title
Visualization and Computer Graphics, IEEE Transactions on
Publisher
ieee
ISSN
1077-2626
Type
jour
DOI
10.1109/TVCG.2014.2346260
Filename
6875920
Link To Document