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GizMO - A customizable representation model for graph-based visualizations of ontologies

: Wiens, V.; Lohmann, S.; Auer, S.


Kejriwal, M. ; Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Artificial Intelligence -SIGART-:
K-CAP 2019, 10th International Conference on Knowledge Capture. Proceedings : November 19-21, 2019, Marina Del Rey, CA, USA
New York: ACM, 2019
ISBN: 978-1-4503-7008-0
International Conference on Knowledge Capture (K-CAP) <10, 2019, Marina del Rey/Calif.>
Fraunhofer IAIS ()

Visualizations can support the development, exploration, communication, and sense-making of ontologies. Suitable visualizations, however, are highly dependent on individual use cases and targeted user groups. In this article, we present a methodology that enables customizable definitions for the visual representation of ontologies.
The methodology describes visual representations using the OWL annotation mechanisms and separates the visual abstraction into two information layers. The first layer describes the graphical appearance of OWL constructs. The second layer addresses visual properties for conceptual elements from the ontology. Annotation ontologies and a modular architecture enable separation of concerns for individual information layers. Furthermore, the methodology ensures the separation between the ontology and its visualization.
We showcase the applicability of the methodology by introducing GizMO, a representation model for graph-based visualizations in the form of node-link diagrams. The graph visualization meta ontology (GizMO) provides five annotation object types that address various aspects of the visualization (e.g., spatial positions, viewport zoom factor, and canvas background color). The practical use of the methodology and GizMO is shown using two applications that indicate the variety of achievable ontology visualizations.