The What and How of Modelling Information and Knowledge by C. Maria Keet

Author:C. Maria Keet
Language: eng
Format: epub
ISBN: 9783031396953
Publisher: Springer Nature Switzerland

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Then if our logic theory has declared that Lindiwe’s house is a house and m1 is still some mud, and the two relate as madeOf(Lindiwe’s house,m1), the reasoner will deduce MudHouse(Lindiwe’s house).

The one other key feature of automated reasoning is inferring the taxonomy, or deducing which class is necessarily a subclass of which other one(s). We modelled that manually in conceptual data models; here, we can get the computer to do that for us. Popular examples in the ontology literature to illustrate it are about pizzas, wine, or vegans and vegetarians. Among the examples in this book, we could revisit the vehicles of Fig. 4.​3 or the scientific database about lyrebirds in Sect. 4.​2.​2.​1. I use an African Wildlife Ontology in my textbook, as it is relevant locally and the rest of the world can daydream about going on a safari. The thing with logic is that we can just as well do without any subject domain and just use A, B, C, ..., since, at the core, it’s about the truth value of a statement in relation to the other, regardless of what we think of when we read a particular term. And also for this reasoning task, there are ‘negative’ examples where things go wrong—like our inconsistent mud house—and ‘positive’ examples where we obtain desirable deductions—as with Lindiwe’s mud house.

A mini-ontology is depicted in Fig. 5.3, with the Description logics axioms side-by-side with abuse of EER notation to visualise them. A could be animal, B carnivore, C herbivore, and D omnivore, say. Whichever example—as long as B and C are subclasses of A and they’re plausibly disjoint and making up A, and there’s some narrative that there are D’s, too, on cursory glance anyway, and that they’re definitely not C’s.

Fig. 5.3 Automated reasoning example before the reasoning, rendered diagrammatically and formalised in a suitable Description Logic (left) and after running the reasoner, with the deductions shown in green (right)

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