science

Weak ontology

Weak ontology is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Weak ontology rather than just read about it. In short: In computer science, a weak ontology is an ontology that is not sufficiently rigorous to allow software to infer new facts without intervention by humans (the end users of the software system). In other words, it does not contain sufficient literal information.

Key takeaways

Weak ontology belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Weak ontology to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Weak ontology from memory before moving on to harder problems.

Reference excerpt

In computer science, a weak ontology is an ontology that is not sufficiently rigorous to allow software to infer new facts without intervention by humans (the end users of the software system). In other words, it does not contain sufficient literal information. By this standard—which evolved as artificial intelligence methods became more sophisticated, and computers were used to model high human impact decisions—most databases use weak ontologies. A weak ontology is adequate for many purposes, including education, where one teaches a set of distinctions and tries to induce the power to make those distinctions in the student. Stronger ontologies only tend to evolve as the weaker ones prove deficient. This phenomenon of ontology becoming stronger over time parallels observations in folk taxonomy about taxonomy: as a society practices more labour specialization, it tends to become intolerant of confusions and mixed metaphors, and sorts them into formal professions or practices. Ultimately, these are expected to reason about them in common, with mathematics, especially statistics and logic, as the common ground. On the World Wide Web, folksonomy in the form of tag schemas and typed links has tended to evolve slowly in a variety of forums, and then be standardized in such schemes as microformats as more and more forums agree. These weak ontology constructs only become strong in response to growing demands for a more powerful form of search engine than is possible with keywording.

References

Worked examples

Example 1 — a first encounter with Weak ontology

Start with the simplest possible case. Write down what Weak ontology claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Weak ontology before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Weak ontology ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Weak ontology

In research: Weak ontology appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Weak ontology in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Weak ontology is common in secondary-school and first-year university syllabi. It links to neighbouring topics Ontology (information science), so understanding it makes those chapters shorter.
In everyday life: Look for Weak ontology outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Weak ontology in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Weak ontology means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Weak ontology out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Weak ontology in simple terms?

Why does Weak ontology matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Weak ontology?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Weak ontology.