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 :
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