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Web Ontology Language

Web 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 Web Ontology Language rather than just read about it. In short: The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects.

Web Ontology Language — main illustration
Web Ontology Language — illustration

Key takeaways

  • Web 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 Web Ontology Language to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Web Ontology Language from memory before moving on to harder problems.

Reference excerpt

The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects. Ontologies resemble class hierarchies in object-oriented programming but there are several critical differences. Class hierarchies are meant to represent structures used in source code that evolve fairly slowly (perhaps with monthly revisions) whereas ontologies are meant to represent information on the Internet and are expected to be evolving almost constantly. Similarly, ontologies are typically far more flexible as they are meant to represent information on the Internet coming from all sorts of heterogeneous data sources. Class hierarchies on the other hand tend to be fairly static and rely on far less diverse and more structured sources of data such as corporate databases. The OWL languages are characterized by formal semantics. They are built upon the World Wide Web Consortium's (W3C) standard for objects called the Resource Description Framework (RDF). OWL and RDF have attracted significant academic, medical and commercial interest. In October 2007, a new W3C working group was started to extend OWL with several new features as proposed in the OWL 1.1 member submission. W3C announced the new version of OWL on 27 October 2009. This new version, called OWL 2, soon found its way into semantic editors such as Protégé and semantic reasoners such as Pellet, RacerPro, FaCT++ and HermiT. The OWL family contains many species, serializations, syntaxes and specifications with similar names. OWL and OWL2 are used to refer to the 2004 and 2009 specifications, respectively. Full species names will be used, including specification version (for example, OWL2 EL). When referring more generally, OWL Family will be used.

History

Early ontology languages

There is a long history of ontological development in philosophy and computer science. Since the 1990s, a number of research efforts have explored how the idea of knowledge representation (KR) from artificial intelligence (AI) could be made useful on the World Wide Web. These included languages based on HTML (called SHOE), based on XML (called XOL, later OIL), and various frame-based KR languages and knowledge acquisition approaches.

Ontology languages for the web In 2000 in the United States, DARPA started development of DAML led by James Hendler. In March 2001, the Joint EU/US Committee on Agent Markup Languages decided that DAML should be merged with OIL. The EU/US ad hoc Joint Working Group on Agent Markup Languages was convened to develop DAML+OIL as a web ontology language. This group was jointly funded by the DARPA (under the DAML program) and the European Union's Information Society Technologies (IST) funding project. DAML+OIL was intended to be a thin layer above RDFS, with formal semantics based on a description logic (DL). DAML+OIL is a particularly major influence on OWL; OWL's design was specifically based on DAML+OIL.

Semantic web standards

The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.

RDF schema

a declarative representation language influenced by ideas from knowledge representation In the late 1990s, the World Wide Web Consortium (W3C) Metadata Activity started work on RDF Schema (RDFS), a language for RDF vocabulary sharing. The RDF became a W3C Recommendation in February 1999, and RDFS a Candidate Recommendation in March 2000. In February 2001, the Semantic Web Activity replaced the Metadata Activity. In 2004 (as part of a wider revision of RDF) RDFS became a W3C Recommendation. Though RDFS provides some support for ontology specification, the need for a more expressive ontology language had become clear.

Web-Ontology Working Group As of Monday, the 31st of May, our working group will officially come to an end. We have achieved all that we were chartered to do, and I believe our work is being quite well appreciated. The World Wide Web Consortium (W3C) created the Web-Ontology Working Group as part of their Semantic Web Activity. It began work on November 1, 2001, with co-chairs James Hendler and Guus Schreiber. The first working drafts of the abstract syntax, reference and synopsis were published in July 2002. OWL became a formal W3C recommendation on February 10, 2004, and the working group was disbanded on May 31, 2004.

OWL Working Group In 2005, at the OWL Experiences And Directions Workshop a consensus formed that recent advances in description logic would allow a more expressive revision to satisfy user requirements more comprehensively whilst retaining good computational properties. In December 2006, the OWL1.1 Member Submission was made to the W3C. The W3C chartered the OWL Working Group as part of the Semantic Web Activity in September 2007. In April 2008, this group decided to call this new language OWL2, indicating a substantial revision. OWL 2 became a W3C recommendation in October 2009. OWL 2 introduces profiles to improve scalability in typical applications.

Acronym Why not be inconsistent in at least one aspect of a language which is all about consistency? OWL was chosen as an easily pronounced acronym that would yield good logos, suggest wisdom, and honor William A. Martin's One World Language knowledge representation project from the 1970s.

Adoption A 2006 survey of ontologies available on the web collected 688 OWL ontologies. Of these, 199 were OWL Lite, 149 were OWL DL and 337 OWL Full (by syntax). They found that 19 ontologies had in excess of 2,000 classes, and that 6 had more than 10,000. The same survey collected 587 RDFS vocabularies.

Ontologies

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Web Ontology Language

Start with the simplest possible case. Write down what Web 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 Web 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 Web 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 Web Ontology Language

In research
Web 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 Web 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
Web Ontology Language is common in secondary-school and first-year university syllabi. It links to neighbouring topics Declarative programming languages, Ontology languages, Resource Description Framework, so understanding it makes those chapters shorter.
In everyday life
Look for Web 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 Web Ontology Language in 20 minutes

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

Frequently asked questions

What is Web Ontology Language in simple terms?

The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects…

Why does Web 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 Web 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 Web Ontology Language.

Tags

  • Declarative programming languages
  • Ontology languages
  • Resource Description Framework
  • Semantic Web
  • Web Ontology Language
  • World Wide Web Consortium standards
  • XML-based standards

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