OWL – an Ontology Language Standard with Sound Logical Underpinning
Submitting InstitutionUniversity of Manchester
Unit of AssessmentComputer Science and Informatics
Summary Impact TypeTechnological
Research Subject Area(s)
Mathematical Sciences: Applied Mathematics
Information and Computing Sciences: Computation Theory and Mathematics, Information Systems
Summary of the impact
Ontologies are used to describe the meaning of terms in a domain.
Manchester has had a leading role in the design of ontology languages,
algorithms and tools. Through standardization, algorithm development and
tool creation, we have significantly influenced the uptake of the Ontology
Web Language (OWL) and Semantic Web Technologies by public service
providers and industry. For example, the NCI thesaurus and SNOMED CT are
medical terminologies in OWL; specialised semantic web companies such as
Clark & Parsia, Racer Systems and TopQuadrant provide semantic
technologies and services that build on OWL; and companies such as Oracle
and B2i Healthcare include tool support for OWL.
By the end of the 1990s, Description Logics (DLs) were well-understood
logical formalisms, e.g., with respect to their computational complexity,
model theory and reasoning services. They were used in niche applications,
but of limited expressive power and with limited tool support — the latter
due to the lack of a standardised syntax. Research carried out in
Manchester dramatically improved the expressive power of and tool support
for DLs, which led to the adoption of DLs as the logical underpinning of
ontology languages, to their standardisation and integration with Semantic
Web infrastructure in OWL and OWL 2, and to their usage in biohealth and
Key researchers from Manchester are:
- Sean Bechhofer (1993 — present: RA, Lecturer 2004, Senior Lecturer
- Ian Horrocks (1996 - 2007: PhD student, RA, Lecturer 1999, Senior
Lecturer 2002, Professor 2003)
- Bijan Parsia (2006 — present: Lecturer, Senior Lecturer 2012)
- Uli Sattler (2003 — present: Senior Lecturer, Professor 2007)
Key research results that underpinned the impact were:
i. Motivated by application examples, the design and investigation of a
range of extensions to existing DLs, establishing various (un)decidability
and computational complexity results [2,3]. In particular, the design of
the SHIQ family of DLs, which show good computational properties
while being highly expressive: they support general concept inclusion,
transitive roles and role hierarchies, inverse roles, cardinality
restrictions and nominals. Each of these features was thought to be
problematic yet desirable, and the research proved that their combination
is of high computational complexity yet decidable.
ii. The design and analysis of reasoning algorithms for SHIQ DLs
[2,3]. These mainly tableau-based algorithms provide sound and complete
decision procedures for the basic DL reasoning problems, and depend on
sophisticated blocking techniques for their termination. The
implementation and optimisation of these algorithms in the FaCT
reasoner provided evidence of their applicability in practice, overcoming
the commonly held belief that such algorithms are impractical .
iii. Investigation of ontology engineering problems, in particular for
modularity, entailment explanation and query answering, and development of
logically sound yet practical solutions for these .
iv. Design and implementation of tools such as ontology-based editors,
reasoners, APIs, and web applications that both showcase the benefits of
OWL for various applications and demonstrate the practicality of the
developed algorithms . The resulting reasoners, editors, and APIs were
highly influential: further research into optimisation in FaCT++
showed that reasoners for complex DLs can indeed cope with large-scale
ontologies; the ontology editor OiLEd was the first one that
exposed ontology designers to a reasoner, and it heavily influenced
Protégé and other editors; and the OWL API is the main API used to
interact programmatically with an ontology and reasoners .
Our research involved a unique combination of investigations of the
computational complexity of logics with informed language, algorithm
design and tool development that changed the general understanding of what
it means for an ontology language to be practical and expressive.
References to the research
Papers that describe this research have been published in international
 I. Horrocks. Using an Expressive Description Logic: FaCT or Fiction?
In Proc. of the 6th Int. Conf. on Principles of Knowledge Representation
and Reasoning (KR'98), pp. 636-647, 1998. [Google Scholar: 575 citations]
KR Outstanding Paper Award.
 I. Horrocks, and U. Sattler. Decidability of SHIQ with complex role
inclusion axioms. Artificial Intelligence, 160 (1-2), pp. 79-104.
2004. DOI: 10.1016/j.artint.2004.06.002 [Google Scholar: 97 citations].
 I. Horrocks and U. Sattler. A Tableaux Decision Procedure for SHOIQ.
Journal of Automated Reasoning, Springer Verlag, 39(3), 245-429,
10.1007/s10817-007-9079-9 [Google Scholar: 419 citations].
 B. Cuenca Grau, I. Horrocks, Y. Kazakov, and U. Sattler. Modular
Reuse of Ontologies: Theory and Practice. Journal of Artificial
Intelligence Research (JAIR), Vol. 31, pp. 273-318, 2008. DOI:/10.1613/jair.2375.
[Google Scholar: 215 citations].
 BC Grau, I Horrocks, B Motik, B Parsia, P Patel-Schneider, U Sattler,
OWL 2: The next step for OWL, J. Web Semantics 6 (4), 309-322,
10.1016/j.websem.2008.05.001 [Google Scholar: 351 citations].
 M. Horridge, S. Bechhofer. The OWL API: A Java API for OWL
ontologies. Semantic Web 2(1): 11-21, 2011. DOI:10.3233/SW-2011-0025.
[Google Scholar: 70 citations].
Details of the impact
There were promising, prototypical implementations of DL reasoners that
were respected in the knowledge representation community, but found little
adoption: the logics were inexpressive, there was limited tool support, no
methodologies, no editors and no standardized syntax.
Pathways to Impact
The research that underpins the impact was reported in high profile
publications that were widely read and cited. Associated with these
publications, several software systems were released that enabled
experimentation with and application of the research results. For example,
the DL reasoners FaCT and FACT++ each received tens of
thousands of downloads, as did OiLEd, the first ontology editor that was
tightly integrated with a DL reasoner, thereby providing a tool to
showcase the feasibility and potential benefits of supporting ontology
engineers through DL reasoning. These tools, together with the OWL API,
led to a wide user base and support by other tool developers, which helped
to establish the utility and maturity of DLs for a range of applications,
including in the web. This, in turn, enabled Horrocks and others to
convince the Semantic Web community to adopt DLs as the logical
foundations of Semantic Web Ontology languages.
Reach and Significance of the Impact
This section describes impacts that have resulted from the research.
Although some of these are economic, there have also been important
impacts on practitioners and service providers through the introduction of
influential de jure standards and changes to best practice, in
particular for the design and development of widely deployed biomedical
Development of Standards in the W3C. The widespread adoption of
the research results has been made possible by the development of World
Wide Web Consortium (W3C) standards for ontology languages and associated
interfaces. These standards are designed by working groups that
have members from outside academia and require serious implementation and
usage efforts to be established. Standards that build directly on
Manchester research, and in which Manchester authors collaborated with
other academics and industrial partners include:
- OWL (2004): the first W3C ontology language standard, which builds on
Manchester research as described in ; contributors: Horrocks and
- OWL 2 (2009): a revision of OWL, heavily driven by the OWL
Experiences and Directions group founded by Horrocks, Parsia, et al.
and by research on qualified number restrictions, key constraints, and
rich property axioms by Horrocks, Parsia, and Sattler; contributors:
Horrocks, Parsia and Sattler.
- SKOS (2009): a standard language for knowledge organisation systems
based on OWL; contributors: Bechhofer.
- SPARQL (2008) and SPARQL 1.1 (2010-12): a query language for RDF and
OWL, influenced by work on OWL query answering by Horrocks and Sattler;
These de jure standards have been widely deployed throughout the
REF period, as described below, thus impacting on practitioners who both
develop and apply semantic web technologies.
Uptake of Reasoning Algorithms and Tools. The standards have
enabled the development of products and tools that in turn have
facilitated the widespread application of semantic web techniques. In this
section we focus principally on two examples:
- Pellet: Pellet, a commercial reasoning system that supports
OWL 2, is marketed by Clark & Parsia, and includes algorithms
developed at Manchester [A]. Pellet has been used by organisations
including NASA, US Army, US Banking Institutions, NATO, NCI, Ordnance
Survey and iPlant Collaborative [A]. In addition, Pellet has been
integrated with and is used in Oracle 11g [A].
- Protégé: Protégé is the most widely used computer system for
engineering ontologies, with 225,000 registered users, and more than
17,000 members of email discussion groups [B]. Protégé supports OWL 2,
the user interface for the current version of Protégé was designed and
implemented at Manchester, and Protégé implements the Manchester OWL API
Manchester techniques and tools, in conjunction with the W3C Standards,
inform other commercial platforms. For example: the commercial reasoner
RacerPro incorporates algorithms designed in Manchester and pioneered in
FaCT, and implements the Manchester OWL API [C]; and the KnowledgeServer
semantic infrastructure of derivo GmbH implements OWL and the OWL API [D].
OWL Tools and Ontologies. Today, thousands of OWL ontologies are
available on the Web. The National Centre for Biomedical Ontologies
BioPortal ontology repository [E] contains 365 OWL ontologies, which are
used in all areas of biomedical activity. The following three ontologies
are amongst the most well established and widely used ones and are built
using OWL and OWL 2:
- SNOMED CT [F], from the International Health Terminology Standards
Development Organisation, is the prime medical thesaurus and is used
worldwide in a variety of healthcare applications, e.g., in NHS
Connecting for Health. The company B2i Healthcare provides specialist
support around OWL and SNOMED CT, in particular Snow OWL [G].
- National Cancer Institute (NCI) Thesaurus [H] is a key biomedical
research vocabulary used in OWL that uses Pellet for classification [A].
- The 11th version of the International Statistical Classification of
Diseases and Related Health Problems (ICD-11) is currently being
developed in OWL under WHO leadership [I]. ICD is used to classify
diseases and other health problems, e.g., in death certificates and
health records. These records also provide the basis for the compilation
of national mortality and morbidity statistics by WHO Member States, and
are used for reimbursement and resource allocation decision-making by
The W3C maintains a list of use-cases of semantic web standards [J] that
detail the users that have built on the standards to which Manchester
contributed. These include: the Norwegian National Broadcaster, Cleveland
Clinic, Ordnance Survey, IBM, National Archives of Korea, Food and
Agriculture Organization of the United Nations, BBC, Chevron, Renault,
Agfa Healthcare and Vodaphone.
Sources to corroborate the impact
Supporting material is available from the university for the
corroborating sources below.
[A] Letter from CEO of Clark & Parsia (http://clarkparsia.com/).
Confirms use of Manchester research in Pellet, and provides details of its
[B] Letter from Professor of Medicine (Biomedical Informatics), Stanford
Centre for Biomedical Informatics Research. Confirms the role of
Manchester research in Protégé, and the scale/nature of the user
[C] Racer Systems GmbH & Co: RacerPro User's Guide, Version 2.0,
October 2012 (http://www.racer-systems.com),
29th August 2013. Confirms the influence of Manchester research
[D] derivo GMBH (http://www.derivo.de/),
on 29th August 2013. Confirms the use of the Manchester OWL
[E] BioPortal: (http://bioportal.bioontology.org/),
on 29th August 2013. Provides information on the number and
scale of biological ontologies.
[F] SNOMED CT Technical Implementation Guide, International Health
Terminology Standards Organisation (www.snomed.org/tig.pdf).
Confirms role of OWL in SNOMED CT.
[G] B2i Healthcare Ltd (http://www.b2international.com/),
on 29th August 2013. Demonstrating a commercial use of OWL.
[H] NCI Thesaurus (http://ncicb.nci.nih.gov/download/evsportal.jsp),
on 29th August 2013. Confirms role of OWL in NCI Thesaurus.
[I] Tudorache T, Falconer S, Nyulas C, Storey MA, Ustün TB, Musen MA.
Supporting the Collaborative Authoring of ICD-11 with WebProtégé. AMIA
Annu Symp Proc. 2010 Nov 13; 2010:802-6, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041458/.
Confirms that ICD-11 uses OWL.
[J] W3C list of use cases: http://www.w3.org/2001/sw/sweo/public/UseCases/,
on 29th August 2013.