ORE has moved to its own separate project. See http://ore-tool.net. The content below is deprecated.
The ORE (Ontology Repair and Enrichment) tool allows for knowledge engineers to improve an OWL ontology by fixing inconsistencies and making suggestions for adding further axioms to it.
Ontology Debugging: ORE uses OWL reasoning to detect inconsistencies and satisfiable classes. State-of-the-art methods are then used to detect the most likely sources for the problems. In a simple process, the user can create a repair plan to resolve a problem, while maintaining full control over desired and undesired inferences.
Ontology Enrichment: ORE uses the DL-Learner framework to suggest definitions and super classes for existing classes in the knowledge base. This works if instance data is available and can be used to detect potential problems and harmonise schema and data in the knowledge base.
Future Work: In future versions, we also aim to support the detection of more modelling problems including non-logical errors. We will also extend support for knowledge bases available as SPARQL endpoints (in contrast to OWL files) and Linked Data.
Tool download: https://github.com/SmartDataAnalytics/ORE
The following screencasts shows how to use the tool:
Basic Screencast (0.1)
Inconsistencies in SPARQL Endpoints (ORE 0.2)
The tool was created by Jens Lehmann and Lorenz Bühmann. If you have any questions or comments, please contact me.
- detection of inconsistencies and unsatisfiable classes
- efficient computation of problematic axioms (justifications)
- fine-grained justifications, e.g. only showing the relevant parts of the axioms to support a minimal semantic repair
- displaying impact of selected repair actions
- enrichment of an ontology by learning definitions and super class axioms using machine learning
- guides the user through potential consequences of adding those axioms
- supports debugging as well as enriching very large knowledge bases available as SPARQL endpoints
- Version 0.2:
- enhanced support for inconsistency detection in large knowledge bases available as SPARQL endpoints
- based on OWL API 3 and Pellet 2
- Version 0.1: initial release