### Ontologies Explained

A blog created by The UWA System Health Lab

OWL (for Engineers)

Published at April 23, 2021 ·  3 min read

Web Ontology Language (OWL) Recap In our prior post we discuss description logics (DLs), a family of mathematical knowledge representation languages which are often used rather than first order logic (FOL) To finish our suite of knowledge representation languages we discuss the Web Ontology Language, usually referred to as OWL. OWL vs DL OWL is another knowledge representation language, based on Description Logics. Unlike description logics and FOL, it is specified as a language which is contained in digital files rather than mathematical symbols....

Transform Disparate Engineering Data into Structured Knowledge

Published at March 22, 2021 ·  12 min read

Transform Disparate Engineering Data into Structured Knowledge Ensure your maintenance strategies are well-informed with RDFox Photo by Ricardo Gomez Angel on Unsplash As engineering companies move towards Industry 4.0, the question of how to leverage the vast amounts of knowledge that they currently store in non-uniform formats must be addressed. In many organisations, critical information is scattered between excel spreadsheets and relational databases (RDBs), which require skilled IT experts to extract the knowledge....

Description Logics (for Engineers)

Published at February 18, 2021 ·  8 min read

Description Logics Why not First Order Logic (FOL)? FOL, which we explained previously, is a knowledge representation language which can be used to express a variety of ideas. Expressivity is a measure of the modelling power of a knowledge representation language. The expressivity of FOL is a double-edged sword. When trying to determine whether particular statements are true, more expressive knowledge representation languages require greater computational resources. FOL is undecidable, meaning that reasoning programs can't be written that are guaranteed to produce correct results without the possibility that they will never terminate (i....

Quantifiers in-depth (for Engineers)

Published at November 11, 2020 ·  4 min read

Introduction In our prior post we discussed First Order Logic (FOL), a useful language for knowledge representation. For example, the following FOL statement expresses that that an electric motor is a type of motor: $$\forall x (ElectricMotor(x) \longrightarrow Motor(x))$$ In greater detail, this can be read as for every possible x ($$\forall x$$) x being an electric motor ($$ElectricMotor(x)$$) implies ($$\longrightarrow$$) x is a motor ($$Motor(x)$$). In this statement, $$ElectricMotor$$ and $$Motor$$ are predicates, $$x$$ is a variable and both $$\forall$$ and $$\longrightarrow$$ are logical symbols....

An Introduction to First Order Logic (for Engineers)

Published at September 18, 2020 ·  12 min read

This is our first blog on the technical aspects of ontologies for engineers. We have taken inspiration from many sources and have created examples relevant to an engineering/maintenance context. First Order Logic First Order Logic (FOL) is a mathematical knowledge representation language used to describe logical concepts and relationships. FOL has many applications. The motivations for using FOL are the unambiguous representation of concepts and the representation of reasoning (how an argument can be represented as a FOL proof)....

Representing Ontologies using First-Order Logic - Lessons Learned

Published at August 20, 2020 ·  7 min read

Representing Ontologies using First-Order Logic - Lessons Learned Creating an ontology for your data has extraordinary benefits (see here for an explanation). When constructing a new ontology, it’s a good idea to do some preliminary work before constructing your model in an Ontology Development Environment (ODE) such as Protégé. This preliminary work is as follows: Identify the generic terms (or “concepts”) needed in your ontology. Discuss these terms and their definitions with a subject matter expert(s) (SME)....

Understanding your data with computational ontology - Part 1

Published at July 14, 2020 ·  3 min read

Databases are everywhere. They come in all shapes (relational, graph, document-based) and sizes. Every time a new software application is created, it often comes with a brand new accompanying database. Along with this database, comes a whole new way of representing information. However, this information is often the same information that is already used in other software applications. To show why this is a problem, consider the following situation:...

Published at June 23, 2020 ·  6 min read

If you are a developer, software architect, or have worked in any data-focused organisation, you might have come across ontologies before. You may have heard about companies or research institutions who have leveraged ontologies to pull their data into a new age of “machine-readability”. If so, you could have tried to explain the benefits of this technology with your boss, only to be met with a blank face....

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