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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.
INDEX TERMS
Ontologies, Data visualization, Biological information theory, OWL, Knowledge representation, VIsual analytics, Data visualization,computer graphics, ontologies, biological data visualization, ontologically annotated texts, visualization of ontologies, network visualization
CITATION
Sheelagh Carpendale, Min Chen, Daniel Evanko, Nils Gehlenborg, Carsten Gorg, Larry Hunter, Francis Rowland, Margaret-Anne Storey, Hendrik Strobelt, "Ontologies in Biological Data Visualization", IEEE Computer Graphics and Applications, vol. 34, no. , pp. 8-15, Mar.-Apr. 2014, doi:10.1109/MCG.2014.33
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