OntoSeer - A Recommendation System to Improve the Quality of Ontologies

Tracking #: 3242-4456

This paper is currently under review
Pramit Bhattacharyya1
Samarth Chauhan
Raghava Mutharaju

Responsible editor: 
Guest Editors Tools Systems 2022

Submission type: 
Tool/System Report
Building an ontology is not only a time-consuming process, but it is also confusing, especially for beginners and the inexperienced. Although ontology developers can take the help of domain experts in building an ontology, they are not readily available in several cases for a variety of reasons. Ontology developers have to grapple with several questions related to the choice of classes, properties, and the axioms that should be included. Apart from this, there are aspects such as modularity and reusability that should be taken care of. From among the thousands of publicly available ontologies and vocabularies in repositories such as Linked Open Vocabularies (LOV) and BioPortal, it is hard to know the terms (classes and properties) that can be reused in the development of an ontology. A similar problem exists in implementing the right set of ontology design patterns (ODPs) from among the several available. Generally, ontology developers make use of their experience in handling these issues, and the inexperienced ones have a hard time. In order to bridge this gap, we developed a tool named OntoSeer, that monitors the ontology development process and provides suggestions in real-time to improve the quality of the ontology under development. It can provide suggestions on the naming conventions to follow, vocabulary to reuse, ODPs to implement, and axioms to be added to the ontology. OntoSeer has been implemented as a Protege plug-in. We conducted a user study of the tool in order to evaluate the quality of the recommendations. Almost all the users are satisfied with the recommendations provided by OntoSeer and a majority of them agreed that OntoSeer reduces their modelling time. The source code and the instructions to install and use the plug-in are publicly available at https://github.com/kracr/ontoseer. A short video demonstrating the use of OntoSeer is available at https://youtu.be/iNQOJGZkZKQ.
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