DocumentCode
48004
Title
Ontologies in Biological Data Visualization
Author
Carpendale, S. ; Min Chen ; Evanko, Daniel ; Gehlenborg, Nils ; Gorg, Carmelita ; Hunter, L. ; Rowland, Francis ; Storey, Margaret-Anne ; Strobelt, Hendrik
Volume
34
Issue
2
fYear
2014
fDate
Mar.-Apr. 2014
Firstpage
8
Lastpage
15
Abstract
In computer science, an ontology is essentially a graph-based knowledge representation in which each node corresponds to a concept and each edge specifies a relation between two concepts. Ontological development in biology can serve as a focus to discuss the challenges and possible research directions for ontologies in visualization. The principle challenges are the dynamic and evolving nature of ontologies, the ever-present issue of scale, the diversity and richness of the relationships in ontologies, and the need to better understand the relationship between ontologies and the data analysis tasks scientists wish to support. Research directions include visualizing ontologies; visualizing semantically or ontologically annotated texts, documents, and corpora; automated generation of visualizations using ontologies; and visualizing ontological context to support search. Although this discussion uses issues of ontologies in biological data visualization as a springboard, these topics are of general relevance to visualization.
Keywords
biology computing; data analysis; data visualisation; graph theory; knowledge representation; ontologies (artificial intelligence); biological data visualization; computer science; corpora; data analysis tasks; graph-based knowledge representation; ontological development; ontologically annotated texts; ontology visualization; semantic text visualization; springboard; Biological information theory; Data visualization; Knowledge representation; OWL; Ontologies; VIsual analytics; biological data visualization; computer graphics; network visualization; ontologically annotated texts; ontologies; visualization of ontologies;
fLanguage
English
Journal_Title
Computer Graphics and Applications, IEEE
Publisher
ieee
ISSN
0272-1716
Type
jour
DOI
10.1109/MCG.2014.33
Filename
6777435
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