science

Ontology language

Ontology language 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 Ontology language rather than just read about it. In short: In computer science and artificial intelligence, ontology languages are formal languages used to construct ontologies. They allow the encoding of knowledge about specific domains and often include reasoning rules that support the processing of that knowledge.

Key takeaways

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

Reference excerpt

In computer science and artificial intelligence, ontology languages are formal languages used to construct ontologies. They allow the encoding of knowledge about specific domains and often include reasoning rules that support the processing of that knowledge. Ontology languages are usually declarative languages, are almost always generalizations of frame languages, and are commonly based on either first-order logic or on description logic.

Classification of ontology languages

Classification by syntax

Traditional syntax ontology languages Common Logic - and its dialects CycL DOGMA (Developing Ontology-Grounded Methods and Applications) F-Logic (Frame Logic) FO-dot (First-order logic extended with types, arithmetic, aggregates and inductive definitions) KIF (Knowledge Interchange Format) Ontolingua based on KIF KL-ONE KM programming language LOOM (ontology) OCML (Operational Conceptual Modelling Language) OKBC (Open Knowledge Base Connectivity) PLIB (Parts LIBrary) RACER

Markup ontology languages These languages use a markup scheme to encode knowledge, most commonly with XML.

DAML+OIL Ontology Inference Layer (OIL) Web Ontology Language (OWL) Resource Description Framework (RDF) RDF Schema (RDFS) SHOE

Controlled natural languages Attempto Controlled English

Open vocabulary natural languages Executable English

Classification by structure (logic type)

Frame-based Three languages are completely or partially frame-based languages.

F-Logic OKBC KM

Description logic-based Description logic provides an extension of frame languages, without going so far as to take the leap to first-order logic and support for arbitrary predicates.

KL-ONE RACER OWL Gellish is an example of a combined ontology language and ontology that is description logic-based. It distinguishes between the semantic differences among others of:

relation types for relations between concepts (classes) relation types for relations between individuals relation types for relations between individuals and classes It also contains constructs to express queries and communicative intent.

First-order logic-based Several ontology languages support expressions in first-order logic and allow general predicates.

Common Logic CycL FO-dot (first-order logic extended with types, arithmetic, aggregates and inductive definitions) KIF

See also Domain theory Formal concept analysis Galois connection Lattice (order) Modeling language OntoUML

Notes

References Oscar Corcho, Asuncion Gomez-Perez, A Roadmap to Ontology Specification Languages (2000) Introduction to Description Logics – DL course by Enrico Franconi, Faculty of Computer Science, Free University of Bolzano, Italy

Worked examples

Example 1 — a first encounter with Ontology language

Start with the simplest possible case. Write down what Ontology language 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 Ontology language 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 Ontology language 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 Ontology language

In research: Ontology language 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 Ontology language 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: Ontology language is common in secondary-school and first-year university syllabi. It links to neighbouring topics Modeling languages, Ontology languages, so understanding it makes those chapters shorter.
In everyday life: Look for Ontology language 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 Ontology language in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Ontology language 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 Ontology language out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Ontology language in simple terms?

Why does Ontology language 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 Ontology language?

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 Ontology language.