# OntoPlot: A Novel Visualisation for Non-hierarchical Associations in   Large Ontologies

**Authors:** Ying Yang, Michael Wybrow, Yuan-Fang Li, Tobias Czauderna, Yongqun He

arXiv: 1908.00688 · 2019-10-24

## TL;DR

OntoPlot is a new visualization tool that effectively displays both hierarchical and non-hierarchical associations in large ontologies, enhancing exploration and understanding for domain experts.

## Contribution

The paper introduces OntoPlot, a hybrid visualization combining icicle plots and interactivity to better represent complex concept associations in large ontologies.

## Key findings

- OntoPlot improves space-efficiency and reduces visual complexity.
- Domain experts prefer OntoPlot over Protégé for association tasks.
- User study confirms OntoPlot's usability and effectiveness.

## 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 Prot{\'e}g{\'e}. The results confirm that OntoPlot attains our design goals for association-related tasks and is strongly favoured by domain experts.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1908.00688/full.md

## Figures

30 figures with captions in the complete paper: https://tomesphere.com/paper/1908.00688/full.md

## References

72 references — full list in the complete paper: https://tomesphere.com/paper/1908.00688/full.md

---
Source: https://tomesphere.com/paper/1908.00688