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Department of Computer Science

Semantic web: Manchester research drives adoption of standardised language

Our research in the field of Description Logics is the foundation for the development of the Web Ontology Language, OWL, adopted by the international web standards body W3C in 2004. The global standard is used in a wide range of semantic applications, in particular in bio-health applications, and is supported by a wide range of tools, several of which have been developed by our research team.

Graphic with head and shoulders silhouette and figure of 225,000


There are 225,000 registered users of the Protégé ontology tool.

There is no doubt that today's search engines and information systems in general are extremely powerful, but even as they return thousands of hits and handle a vast number of documents, they do not really understand the meaning of the text they search or process. For example, searching "mammal cull" on the BBC website returns very few results, whereas searching "badger cull" returns hundreds of news items—despite the fact that badgers are mammals.

Semantic systems, however, take searching and document analysis to a whole new level. Semantic technologies capture and take into account the meaning of words such as "badger" and "mammals"; for example, they allow the system designer to add biological background such as badgers being mammals and omnivores, and living in sets. This way, text is made 'understandable' for computers—so that a (semantic) search can return articles on badger culls when asked for mammal culls.

Research to develop languages that, on the one hand, allows human users to describe the meaning of words and, on the other hand, a computer to process these descriptions, began in the late 1980s, and led to what we now call ontology languages, in particular OWL. Researchers from the Department of Computer Science played a pivotal role in this international effort. Specifically, they played central roles designing these languages based on logic, namely so-called 'Description Logics', and demonstrated that they are suitable by developing powerful tools to process and engineer ontologies in these languages.

Setting the standard

The work of our team helped to persuade the international web standards body, W3C, to adopt the above mentioned Description Logics as the foundation for a new internationally standardised ontology language. Today the Web Ontological Language (OWL) is used in a large number of ontologies for a variety of applications.

We have made major contributions to four international standards (known as "W3C Recommendations"):

  • OWL (2004): the first W3C ontology language standard.
  • OWL 2 (2009): a revision of OWL, heavily driven by the OWL Experiences and Directions Group.
  • SKOS (2009): a standard language based on OWL for knowledge organisation systems.
  • SPARQL (2008) and SPARQL 1.1 (2010-12): a query language for OWL, influenced by our research into OWL query answering.

Tools and software

Numerous tools and software comply with OWL and related standards. The following three widely used tools all received direct input and development from the Manchester team.

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Medical ontologies

365 specialist biomedical ontologies published by the National Center for Biomedical Ontology.

Fact++ is an ontology reasoner, ie a piece of software that takes an ontology with its description of terms and their meaning, and processes these descriptions to find new, implicit relationships between them and to answer questions about them.

OWL API is a Java interface that allows programmers to build software that access ontologies and uses ontology reasoners such as Fact++ or Pellet; the latter is a commercial reasoning system marketed by Clark and Parsia. Pellet is used for semantic data analysis by organisations including NASA, US Army, US banking institutions, NATO, NCI, Ordnance Survey and iPlant Collaborative. It is also integrated into the Oracle Database 11g platform.

Protégé is a widely used tool for creating ontologies for semantic applications, boasting 225,000 registered users worldwide and tightly integrated with the above mentioned reasoners.

Ontologies on the increase

Today, thousands of OWL ontologies are available, providing structured terminology definitions in a range of disciplines, especially biology and health. For example, the National Center for Biomedical Ontology manages a repository of over 360 OWL ontologies which are used in all areas of biomedical activity.

Other open-source ontologies include:

  • SNOMED CT, a general medical thesaurus used around the world.
  • The National Cancer Institute Thesaurus, a medical ontology developed by the US American National Cancer Institute.
  • The 11th version of the International Statistical Classification of Diseases and Related Health Problems. ICD-11, is a revision of ICD-10, which is used worldwide to classify diseases and other health problems for national statistics, government decision-making and international public health research.


From the mid-1990s, researchers in the Department of Computer Science began to investigate the feasibility of using description logics (DLs) as the basis for building hierarchical, structured definitions of terminologies for specific subjects.

Our work dramatically improved the power of DLs. We also created new tools which brought our methods for semantic computation to a much wider group of users. Our findings were embraced by W3C which adopted DLs and many of our specific research outputs in its development of the international standard Web Ontological Language (OWL).

Key research outputs:

  • Design of the SHIQ family of description logics which solved many of the problems first associated with semantic computation.
  • The design and analysis of reasoning algorithms for SHIQ.
  • Implementation and optimisation of SHIQ reasoning algorithms in the FaCT reasoner, proving the practical application of the Manchester approach.
  • Insights into ontology engineering, in particular the use of modularity, entailment explanation and query answering.
  • Demonstration that reasoners for complex DLs can cope with large-scale ontologies.
  • Design and implementation of many tools – reasoners, editors and APIs – to showcase research results and demonstrate the benefits of OWL.