Description Logics as Ontology Languages
for the Semantic Web
Franz Baader1, Ian Horrocks2, and Ulrike Sattler1
1 Theoretical Computer Science, RWTH Aachen, Germany
{baader,sattler}@cs.rwth-aachen.de
2 Department of Computer Science, University of Manchester, UK
horrocks@cs.man.ac.uk
Abstract. The vision of a Semantic Web has recently drawn consider-
able attention, both from academia and industry. Description logics are
often named as one of the tools that can support the Semantic Web and
thus help to make this vision reality.
In this paper, we describe what description logics are and what they can
do for the Semantic Web. Descriptions logics are very useful for defining,
integrating, and maintaining ontologies, which provide the Semantic Web
with a common understanding of the basic semantic concepts used to
annotate Web pages. We also argue that, without the last decade of basic
research in this area, description logics could not play such an important
roˆle in this domain.
1 Introduction
The goal of this introduction is to sketch, on an informal level, what the Se-
mantic Web is, why it needs ontologies, and where description logics come into
play. Regarding the last point, we will first give a brief introduction to descrip-
tion logics, and then argue why they are well-suited as ontology languages. The
remainder of this paper will then put some flesh on this skeleton by providing
more technical details.
The Semantic Web and Ontologies
For many people, the World Wide Web has become an indispensable means of
providing and searching for information. Searching the Web in its current form
is, however, often an infuriating experience since today’s search engines usually
provide a huge number of answers, many of which are completely irrelevant,
whereas some of the more interesting answers are not found. One of the rea-
sons for this unsatisfactory state of affairs is that existing Web resources are
usually only human understandable: the mark-up (HTML) only provides ren-
dering information for textual and graphical information intended for human
consumption.
The Semantic Web [15] aims for machine-understandable Web resources,
whose information can then be shared and processed both by automated tools,
such as search engines, and by human users. In the following we will refer to con-
sumers of Web resources, whether automated tools or human users, as agents.
D. Hutter, W. Stephan (Eds.): Mechanizing Mathematical Reasoning, LNAI 2605, pp. 228–248, 2005.
c© Springer-Verlag Berlin Heidelberg 2005

Description Logics as Ontology Languages for the Semantic Web 229
This sharing of information between different agents requires semantic mark-up,
i.e., an annotation of the Web page with information on its content that is un-
derstood by the agents searching the Web. Such an annotation will be given in
some standardized, expressive language (which, e.g., provides Boolean operators
and some form of quantification) and make use of certain terms (like “Human”,
“Plant”, etc.). To make sure that different agents have a common understanding
of these terms, one needs ontologies in which these terms are described, and
which thus establish a joint terminology between the agents. Basically, an ontol-
ogy [44, 43] is a collection of definitions of concepts and the shared understanding
comes from the fact that all the agents interpret the concepts w.r.t. the same
ontology.
The use of ontologies in this context requires a well-designed, well-defined,
and Web-compatible ontology language with supporting reasoning tools. The
syntax of this language should be both intuitive to human users and compatible
with existing Web standards (such as XML, RDF, and RDFS). Its semantics
should be formally specified since otherwise it could not provide a shared un-
derstanding. Finally, its expressive power should be adequate, i.e., the language
should be expressive enough for defining the relevant concepts in enough detail,
but not too expressive to make reasoning infeasible.
Reasoning is important to ensure the quality of an ontology. It can be em-
ployed in different development phases. During ontology design, it can be used
to test whether concepts are non-contradictory and to derive implied relations.
In particular, one usually wants to compute the concept hierarchy. Information
on which concept is a specialization of another and which concepts are synonyms
can be used in the design phase to test whether the concept definitions in the
ontology have the intended consequences or not. Moreover, this information is
also useful when searching Web pages annotated with such concepts. Since it
is not reasonable to assume that there will be a single ontology for the whole
Web, interoperability and integration of different ontologies is also an important
issue. Integration can, for example, be supported by asserting inter-ontology
relationships and testing for consistency and computing the integrated concept
hierarchy. Finally, reasoning may also be used when the ontology is deployed, i.e.,
when a Web page is already annotated with its concepts. One can, for example,
determine the consistency of facts stated in the annotation with the ontology or
infer instance relationships. However, in the deployment phase, the requirements
on the efficiency of reasoning are much more stringent than in the design and
integration phases.
Before arguing why description logics are good candidates for such an on-
tology language, we provide a brief introduction to and history of description
logics.
Description Logics
Description logics (DLs) [7, 24] are a family of knowledge representation lan-
guages that can be used to represent the knowledge of an application domain in
a structured and formally well-understood way. The name description logics is