21
Chapter 2
Ontology: Fundamentals
and Languages
Rajendra Akerkar
Vestlandsforsking, Sogndal, Norway
Contents
2.1 Introduction ...............................................................................................22
2.1.1 Denitions ......................................................................................23
2.1.2 Taxonomy, esauri, and Ontology ................................................25
2.1.3 Properties and Characteristics .........................................................29
2.2 Types of Ontologies ....................................................................................29
2.3 Parameters for Building Ontologies ............................................................30
2.4 Standards and Interoperability ...................................................................31
2.5 Semantic Web and Ontology .....................................................................32
2.6 Applications ...............................................................................................33
2.6.1 Knowledge Management ................................................................33
2.6.2 Enterprise Application Integration ................................................. 34
2.6.3 e-Commerce .................................................................................. 34
2.6.4 e-Learning ..................................................................................... 34
2.7 Reasoning ..................................................................................................35
2.8 Ontology Languages ..................................................................................36
2.8.1 Frame-Based Languages .................................................................36
2.8.2 Logic-Based Languages ...................................................................38
2.8.3 Ontology Representation Languages...............................................39
2.8.3.1 XML Schema .................................................................. 40
22  ◾  Rajendra Akerkar
2.1 Introduction
e vision of the Semantic Web is to enable machines to interpret and process
information on the World Wide Web to provide quality support to mankind in
carrying out various tasks involving information and communication technology.
e challenge of the Semantic Web is to provide necessary information with well-
dened meanings, understandable by dierent parties and machines in such a way
that applications can provide customized access to information by meeting the
individual needs and requirements of the users.
Several technologies have been developed for shaping, constructing, and develop-
ing the Semantic Web. Ontology plays an important role as a source of formally dened
terms for communication. e prime objective of ontology is to facilitate knowledge
sharing and reuse on a distributed platform. While some dispute surrounds what encom-
passes ontologies, they generally include a taxonomy of terms, and several ontology lan-
guages allow supplementary denitions using some kind of logic. Moreover, although
the words ontology and vocabulary are often used interchangeably, a vocabulary is a
collection of terms used in a specic domain; it can be hierarchically arranged as a
taxonomy, and combined with rules, constraints, and relationships to form an ontology.
Ontology creation consists of dening all ontology components through an ontology
denition language. Creation is initially an informal process using either natural lan-
guage or diagram technique. e ontology is encoded in a formal knowledge represen-
tation language such as RDF schema or Web ontology language (OWL). is chapter
introduces ontology fundamentals and languages and discusses ontology and OWL at
a certain level of detail to enable the reader to see the potential of the language.
e next subsection presents terminology for taxonomy, thesauri, and ontology
and will cover various issues related to ontology and its applications. Section 1.2
2.8.3.2 RDF Schema ....................................................................45
2.8.3.3 Web Ontology Language ................................................. 46
2.8.4 OWL 2 Proles ...............................................................................57
2.9 Integration of Ontology and Rule Languages .............................................57
2.10 Ontology-Driven Information Integration .................................................58
2.11 Ontology Tools ..........................................................................................59
2.11.1 Protégé ............................................................................................59
2.11.2 OntoEdit ........................................................................................59
2.11.3 KAON2 ..........................................................................................59
2.11.4 Pellet ...............................................................................................60
2.11.5 FaCT++ ...........................................................................................60
2.11.6 TopBraid Composer ........................................................................60
2.11.7 SemanticWorks ...............................................................................61
2.11.8 CMapTools Ontology Editor (COE) ...............................................61
2.11.9 Other Tools ....................................................................................61
References ...........................................................................................................62
Ontology: Fundamentals and Languages  ◾  23
presents types of ontologies. Section 1.3 discusses construction parameters. Sections
1.4 and 1.5 deal with interoperability and Semantic Web issues. Section 1.6 explains
traditional application areas for ontology. Reasoning issues are presented in Section
1.7. Section 1.8 discusses ontology languages, including representation types such
as XML schema and RDF schema, to provide contexts for understanding OWL.
We also discuss the basics of OWL—properties and examples. Section 1.9 describes
integration of ontology and rule languages. Section 1.10 describes ontology-driven
information integration. Finally, Section 1.11 presents useful Semantic Web tools.
2.1.1 Definitions
In the broad context of the Semantic Web, applications must be understood by
machine, with the help of a meaning associated with each component stored on
the Web. Such capability of understanding is not covered by the traditional tools
like markup languages and protocols utilized on the World Wide Web platform.
A component representation scheme called ontology is a requirement. Ontology
interweaves human and computer understandings and interpretations of symbols
(also known as terms). Ontology provides means for conceptualizing and structur-
ing knowledge and allows semantic annotation of resources to support information
retrieval, automated inference, and interoperability among services and applica-
tions across the Web.
Ontologies provide in-depth characteristics and classes such as inverses, unam-
biguous properties, unique properties, lists, restrictions, cardinalities, pair-wise dis-
joint lists, data types, and so on. Ontologies often allow objective specication of
domain information by representing a consensual agreement on the concepts and
relations that characterize the manner in which knowledge in a domain is expressed.
is specication can be the rst step in building semantically aware informa-
tion systems to support diverse enterprise, government, and personal activities. e
original denition of ontology comes from the eld of philosophy (Denition 1) and
is included in Webster’s Revised Unabridged Dictionary (http://www.dict.org/). e
more modern Denition 2 relates to systems.
Denition 1—at department of the science of metaphysics which investi-
gates and explains ontology as the nature and essential properties and relations of
all beings, as such, or the principles and causes of being.
Denition 2—Ontology is an abstract model which represents a common and
shared understanding of a domain.
e word ontology has a very long history in philosophy starting with the works
of Aristotle. Dened as the science of being, it comes from the Greek ontos (being)
and logos (language or reason). Ontology is then the branch of metaphysics that
deals with the nature of being. From the view of phenomenology, a more modern
philosophy that started with the 19th century German philosophers, ontology is a
systematic account of existence. However, based on a phenomenological approach,
being and existence are dierent notions and cannot be combined or considered
24  ◾  Rajendra Akerkar
simultaneously. While philosophers build ontology from the top down, practitio-
ners of computer science usually build an ontology from the bottom up.
As a matter of fact, one can retain three dimensions in an ontology: knowledge,
language, and logic, i.e., language to speak about the world, conceptualization to
understand the world, and representation to manipulate our understanding.
Ontology has been a well-known concept for many years in the articial intel-
ligence and knowledge representation communities. It addresses ways of represent-
ing knowledge so that machines can reason and thus make valid deductions and
inferences. Ontology generally consists of a list of interrelated terms and inference
rules and can be exchanged between users and applications. An ontology may be
dened in a more or less formal way, from natural language to description logics.
OWL belongs to the latter category. It is built upon RDF and RDFS and extends
them to express class properties. e pioneer denition of ontology in the sense of
the Semantic Web was proposed by Tom Gruber (Gruber, 1993):
Denition 3—Ontology is a formal explicit specication of a shared
conceptualization.
In the 1990s, knowledge engineers borrowed the ontology term as a systematic
account of existence rather than a metaphysical approach of the nature of being.
As a matter of fact, for articial intelligence systems, what exists is that which can
be represented in a declarative language. Ontology is then an explicit formal speci-
cation of how to represent objects, concepts, and relationships assumed to exist
in some area of interest—what Gruber called “a specication of a conceptualisa-
tion” (like a formal specication of a program) of the concepts and relationships of
an agent or a community of agents. A conceptualization is an abstract simplied
view of the world that one wishes to represent for some purpose. e ontology is a
specication because it represents conceptualization in a concrete form. It is explicit
because all concepts and constraints used are explicitly dened. Formal means the
ontology should be machine understandable. Shared indicates that the ontology
captures consensual knowledge.
Ontology-based semantic structures replace the jumbles of ad hoc rule-based
techniques common to earlier knowledge representation systems. is makes
knowledge representation languages easy to manage by combining logic and ontol-
ogy. In the context of the Semantic Web, we can further modify the ontology
denition as follows:
Denition 4—Computer ontologies are formally specied models of known
knowledge in a given domain.
Metadata and ontology are complementary and constitute the Semantic Web’s
building blocks. ey avoid meaning ambiguities and provide more precise answers.
In addition to better query result accuracy, another goal of the Semantic Web is
to describe the semantic relationships of the answers. Any general ontology model
represents only a consensual agreement on the concepts and relations that char-
acterize the way knowledge in a domain is expressed. Higher level ontology may
simply model common knowledge instead of specic data. Important notions in
Ontology: Fundamentals and Languages  ◾  25
connection with Web-related ontology are a vocabulary of basic terms and a pre-
cise specication of their meanings. e consensus standard vocabularies can be
handled by dening reusable vocabularies, and customizing and extending them. A
number of well-known ontologies arose from linguistics and knowledge engineer-
ing areas:
◾ WordNet is a top-down ontology (in upper layer) in the linguistic domain con-
taining a structured English language vocabulary with lexical categories and
semantic relations.
◾ Cyc is a common ontology consisting of knowledge captured from dierent
domains.
◾ SENSUS is a linguistic domain ontology built by extracting and merging infor-
mation from existing electronic resources for the purpose of machine translation.
2.1.2 Taxonomy, Thesauri, and Ontology
Taxonomy is a science of classication that provides guidelines about how to cat-
egorize, organize, label, and arrange information in hierarchical fashion. It can be
considered classication based on similarities. Taxonomy includes presentations of
vocabularies, application proles, and development of metadata schemes, if any.
Taxonomies and thesauri do not appear on the Semantic Web stack as they were
not specically designed for the Web; they, however, belong to the Semantic Web
picture. e taxonomy can be dened as follows:
Denition 5—Taxonomy is a hierarchically organized controlled vocabulary.
e world has a number of taxonomies, because humans naturally classify objects.
Taxonomies are semantically weak and are commonly used when navigating with-
out a precise research goal in mind.
As an example, a sample taxonomy from a typical tourism area is presented in
this section. A tourism destination is primarily described by enumerating its fea-
tures. However, since a taxonomy is only a collection of names, each item of a tour-
ism area taxonomy must be characterized so that each description carries interesting
information about the destination. is requires a vocabulary of terms that represent
relevant concepts. Figure2.1 illustrates a common (but incomplete) vocabulary that
may serve this purpose. e relative meanings of the terms are reected in the taxo-
nomic ordering. e leaf terms are primary; the other terms are secondary and may
be introduced by terminological denitions.
A thesaurus is intended to facilitate document retrieval. WordNet organizes
English nouns, verbs, adverbs, and adjectives into a set of synonyms and denes
relationships among synonyms.
Denition 6—A thesaurus is a controlled vocabulary arranged in a known
order and structured so that equivalence, homographic, hierarchical, and associa-
tive relationships among terms are displayed clearly and identied by standardized
relationship indicators.
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