OntoGen is a semi-automatic and data-driven ontology editor focusing on editing of topic ontologies (a set of topics connected with different types of relations). The system combines text-mining techniques with an efficient user interface to reduce both: the time spent and complexity for the user. In this way it bridges the gap between complex ontology editing tools and the domain experts who are constructing the ontology and do not necessarily have the skills of ontology engineering.
The main characteristics
- Semi-Automatic – The system is an interactive tool that aids the user during the ontology construction process. It suggests: concepts, relations between the concepts, names for the concepts, automatically assigns instances to the concepts, visualizes instances within a concept and provides a good overview of the ontology to the user through concept browsing and various kinds of visualizations. At the same time the user is always in full control of the systems actions and can fully adjust all the properties of the ontology by accepting or rejecting the system’s suggestions or manually adjusting them. This enables the user to establish trust in the system in a way that he has a full control over all the modifications to the edited ontology.
- Data-Driven – Most of the aid provided by the system is based on the underlying data provided by the user typically at the beginning of the ontology construction. The data reflects the structure of the domain for which the user is building ontology. The data is provided as a document corpus where ontological instances are either documents themselves or name-entities occurring in the documents. The system supports automatic extraction of instances (used for learning concepts) and co-occurrences of instances (used for learning relations between the concepts) from the data.