Научная визуализация, 2020, том 12, номер 4, страницы 71 - 84, DOI: 10.26583/sv.12.4.07
Developing Non-Empirical Metrics and Tools for Ontology Visualizations Evaluation and Comparing
Авторы: I. Baimuratov1, Th. Nguyen2, R. Golchin3, D. Mouromtsev4
ITMO University, Kronverksky Pr. 49, bldg. A, St. Petersburg, 197101, Russia
1 ORCID: 0000−0002−6573−131X, baimuratov.i@gmail.com
2 ORCID: 0000−0002−6679−7839
3 ORCID: 0000−0003−0485−4014
4 ORCID: 0000−0002−0644−9242
Аннотация
There are numerous ontology visualization systems, however, the choice of a visualization system is non-trivial, as there is no method for evaluation and comparing them, except for empirical experiments, that are subjective and costly. In this research, we aim to develop non- empirical metrics for ontology visualizations evaluation and comparing. First, we propose several half-formal metrics that require expert evaluation. These metrics are completeness, semanticity, and conservativeness. We apply the proposed metrics to evaluate and compare VOWL, Graphol and Logic Graphs visualization systems. And second, we develop a completely computable measure for the complexity of ontology visualizations, based on graph theory and information theory. In particular, ontology visualizations are considered as hypergraphs and the information measure is derived from the Hartley function. The usage of the proposed information measure is exemplified by the evaluation of visualizations of the sample of axioms from the DoCO ontology in Logic Graphs and Graphol. These results can be practically applied for choosing ontology visualization systems in general and regarding a particular ontology. The application for ontology visualization evaluation and comparing based on the formal metrics is provided.
Ключевые слова: Ontology Visualization, Expert Evaluation, Hypergraphs, Information Measure.
