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Thinking like an OWL reasoner

Publication date: Sep 17, 2011

This paper shows the principles underlying the functionality of semantic reasoners using a set of examples consisting of simple shapes and colors.

This is a guest contribution by Peter Hendler MD, practicing physician, computer scientist and chair of the HL7 RIMBAA working group.

Closed and Open worlds

Although there are excellent sources (especially the OWL pizza tutorial) to learn how to model in OWL, there are none that I have found to teach you how to think like a reasoner. People who are familiar and live in the closed Object Oriented or Relational Dabase worlds often have difficulty thinking in the Open World OWL way. It took me quite a while to get my mind around this different way of thinking. The fact that OWL has "classes and subclasses" doesn't help because these classes don't behave at all like the "normal" classes we all work with in Java and C#.

Reasoner

Once I understood what the reasoner was doing, I found it almost impossible to explain because if I use examples where people know what the "words mean", they then focus on the meaning of the words and often get side tracked.

It's important to realize that to a reasoner, all the labels we attach to a concept are meaningless words and might as well be random numbers. This means that not only must you ignore the meaning of the words (which is hard to do) but you can't even conclude obvious things like a tuna fish is not the same as a television. To the reasoner it might be.

For example, if I create something I call person and someone else creates another thing they call human they might in fact represent the same thing. Since the reasoner can not understand words, it has to assume that no matter what the words say, they might or might not be the same thing.

I wanted to come up with a way of explaining how the reasoner works that completely ignores the words used to represent, concepts, parents and relationships. This video is an attempt to explain what the reasoner does using only colors and shapes. The algorithm used in this video is not the actual one reasoners use, but it is by far the easiest to comprehend and results in the same answers.

Peter

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