These are my notes for Alan Bundy’s and Ewen Maclean’s talk at the UK Ontology Network Meeting on 14 April, 2016.
This talk is divided into two parts: Merging Ontologies via Analogical Blending, and Repairing Faulty Ontologies using Reformation.
Can you merge ontologies successfully using analogical blending? It would be quite easy to get things wrong, and therefore they are using the reformation technique to repair any mistakes made in the merging process.
T1 and T2 are the parent theories, and B is the blend between them. Suppose T1 and T2 are two retailer ontologies. T1 has relationships for owning, and part numbers, and product A and product B have the same part number as they are different instances of the same product. In T2, the relationship is sold_to and there are serial numbers rather than part numbers. So, things are similar but not identical. It would be easy to automatically align these concepts incorrectly. When the ontology is merged, the two products are incorrectly given the same serial number (when they only have the same part number). This makes the ontology inconsistent.
How can the reformation technique help you recover? Reformation works from reasoning failures. Here, we’re looking into inconsistencies. Using the proof of inconsistency, reformation tries to break the proof to prevent it from getting to the inconsistency, and therefore creating a suggested repair, in this case rename the two occurrences of the serial number. The resulting new blended ontology has replaced the serial number type with a part number type, and part and serial number are two different types, thus correcting the ontology.
Ontologies can be merged by analogical blending, but some blends can be faulty. Faults can be revealed by reasoning failures. Reformation uses such failures to diagnose and repair faulty ontologies. This work is still in the early stages.
Please note that this post is merely my notes on the presentation. I may have made mistakes: these notes are not guaranteed to be correct. Unless explicitly stated, they represent neither my opinions nor the opinions of my employers. Any errors you can assume to be mine and not the speaker’s. I’m happy to correct any errors you may spot – just let me know!