Abstract
We are proposing a semantic approach that aims to identify valid linguistic web services composition scenarios. It targets both linguistic and software engineering experts. It is based on an OWL2 multilingual ontology, named LingOnto which models and reasons about linguistic knowledge. However, users especially non-ontology experts have difficulty to make sense of LingOnto as they do not understand its syntax. Hence, we decide to visualize LingOnto to attempt this issue. Nevertheless, the heterogeneity and the amount number of linguistic knowledge make the visualisation hard to comprehend due to visual clutter and information overload. In this paper, we propose a user-friendly ontology visualisation tool, named Ling-Graph. It targets both ontology and non-ontology experts and addresses the readability and understandability requirements. Ling-Graph is based on a “smart” search interaction technique, to extract and visualize, from LingOnto, a dynamic ontological view that contains only components corresponding to the user’s need. It is relied on a SPARQL patterns-based approach which takes the user’s need materialized by a set of search criteria as input and generates the ontological view that matches these criteria. The obtained tool is also applied to visualize the PersonLink ontology for non-ontology experts and a large-scale ontology DBpedia for ontology experts. Finally, we discuss the promising results derived from the evaluation of Ling-Graph.
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Neji, M., Ghorbel, F., Gargouri, B. (2019). A Smart Search-Based Ontology Visualization Tool Using SPARQL Patterns. In: Douligeris, C., Karagiannis, D., Apostolou, D. (eds) Knowledge Science, Engineering and Management. KSEM 2019. Lecture Notes in Computer Science(), vol 11775. Springer, Cham. https://doi.org/10.1007/978-3-030-29551-6_4
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