OntoPlot: a novel visualisation for non-hierarchical associations in large ontologies

Ying Yang, Michael Wybrow, Yuan Fang Li, Tobias Czauderna, Yongqun He

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

Ontologies are formal representations of concepts and complex relationships among them. They have been widely used to capture comprehensive domain knowledge in areas such as biology and medicine, where large and complex ontologies can contain hundreds of thousands of concepts. Especially due to the large size of ontologies, visualisation is useful for authoring, exploring and understanding their underlying data. Existing ontology visualisation tools generally focus on the hierarchical structure, giving much less emphasis to non-hierarchical associations. In this paper we present OntoPlot, a novel visualisation specifically designed to facilitate the exploration of all concept associations whilst still showing an ontology's large hierarchical structure. This hybrid visualisation combines icicle plots, visual compression techniques and interactivity, improving space-efficiency and reducing visual structural complexity. We conducted a user study with domain experts to evaluate the usability of OntoPlot, comparing it with the de facto ontology editor Protégé. The results confirm that OntoPlot attains our design goals for association-related tasks and is strongly favoured by domain experts.

Original languageEnglish
Article number8809833
Pages (from-to)1140-1150
Number of pages11
JournalIEEE Transactions on Visualization and Computer Graphics
Volume26
Issue number1
DOIs
Publication statusPublished - Jan 2020

Keywords

  • interactive exploration
  • ontology associations
  • Ontology visualisation
  • visual compression

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