Literature DB >> 24808195

Ontologies in biological data visualization.

Sheelagh Carpendale, Min Chen, Daniel Evanko, Nils Gehlenborg, Carsten Gorg, Larry Hunter, Francis Rowland, Margaret-Anne Storey, Hendrik Strobelt.   

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.

Mesh:

Year:  2014        PMID: 24808195     DOI: 10.1109/MCG.2014.33

Source DB:  PubMed          Journal:  IEEE Comput Graph Appl        ISSN: 0272-1716            Impact factor:   2.088


  1 in total

1.  Pathways for Theoretical Advances in Visualization.

Authors:  Min Chen; Georges Grinstein; Chris R Johnson; Jessie Kennedy; Melanie Tory
Journal:  IEEE Comput Graph Appl       Date:  2017       Impact factor: 2.088

  1 in total

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