web semantics and ontology

Web Semantics
and Ontology
David Taniar, Monash University, Australia
Johanna Wenny Rahayu, La Trobe University, Australia
Hershey • London • Melbourne • Singapore
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Library of Congress Cataloging-in-Publication Data
Web semantics and ontology / David Taniar and Johanna Wenny Rahayu, editors.
p. cm.
Summary: "This book provides an overview of current research and development activities in the area
of web semantics and ontology, giving an in-depth description of different issues, including modeling,
using ontologies in enterprise systems, querying and knowledge discovering of ontologies" Provided by
publisher.
Includes bibliographical references and index.
ISBN 1-59140-905-5 (hardcover) ISBN 1-59140-906-3 (softcover) ISBN 1-59140-907-1
(ebook)
1. Semantic Web. 2. Ontology. I. Taniar, David. II. Rahayu, Johanna Wenny.
TK5105.88815.W42 2006
025.04 dc22
British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book is new, previously-unpublished material. The views expressed in this
book are those of the authors, but not necessarily of the publisher.
Web Semantics
and Ontology
Table of Contents
Preface vi
Section I. Web Semantics and Ontologies Modelling
Chapter I. Ontology Extraction Using Views for Semantic Web 1
Carlo Wouters, La Trobe University, Australia

Rajugan Rajagopalapillai, University of Technology, Sydney,
Australia
Tharam S. Dillon, University of Technology, Sydney, Australia
Wenny Rahayu, La Trobe University, Australia
Chapter II. Representation of Web Application Patterns in OWL 41
Pankaj Kamthan, Concordia University, Canada
Hsueh-leng Pai, Concordia University, Canada
Chapter III. Contextual Ontology Modeling Language to
Facilitate the use of enabling Semantic Web Technologies 68
Laura Caliusco, Universidad Tecnológica Nacional - FRSF,
Argentina
César Maidana, Universidad Tecnológica Nacional - FRSF,
Argentina
Maria R. Galli, INGAR-CONICET-UTN, Argentina
Omar Chiotti, INGAR-CONICET-UTN, Argentina
Section II. Ontologies and Enterprise Systems
Chapter IV. Ontology Management for Large-Scale Enterprise
Systems 91
Juhnyoung Lee, IBM T.J. Watson Research Center, USA
Richard Goodwin, IBM T.J. Watson Research Center, USA
Rama Akkiraju, IBM T.J. Watson Research Center, USA
Chapter V. From Ontology Phobia to Contextual Ontology Use
in Enterprise Information Systems 115
Rami Rifaieh, University of California San Diego, USA
Aïcha-Nabila Benharkat, National Institute of Applied
Science of Lyon, France
Chapter VI. A Comparison of Semantic Annotation Systems for
Text-Based Web Documents 165
Lawrence Reeve, Drexel University, USA
Hyoil Han, Drexel University, USA

Section III. Ontologies-Based Querying and Knowledge Discovery
Chapter VII. Ontology Enhancement for Including Newly
Acquired Knowledge About Concept Descriptions and
Answering Imprecise Queries 189
Lipika Dey, Indian Institute of Technology, Delhi, India
Muhammad Abulaish, Jamia Millia Islamia, India
Chapter VIII. Dynamic Knowledge Discovery in Open,
Distributed and Multi-Ontology Systems: Techniques and
Applications 226
Silvana Castano, Università degli Studi di Milano, Italy
Alfio Ferrara, Università degli Studi di Milano, Italy
Stefano Montanelli, Università degli Studi di Milano, Italy
Chapter IX. Metadata- and Ontology-Based Semantic Web
Mining 259
Marie Aude Aufaure, Supélec, France
Bénédicte Le Grand, Laboratoire d’Informatique de Paris 6,
France
Michel Soto, Laboratoire d’Informatique de Paris 6, France
Nacera Bennacer, Supélec, France
Section IV. Applications and Policies
Chapter X. Translating the Web Semantics of Georeferences 297
Stephan Winter, The University of Melbourne, Australia
Martin Tomko, The University of Melbourne, Australia
Chapter XI. Ontological Engineering in Pervasive Computing
Environments 334
Athanasios Tsounis, University of Athens, Greece
Christos Anagnostopoulos, University of Athens, Greece
Stathes Hadjiethymiades, University of Athens, Greece
Izambo Karali, University of Athens, Greece
Chapter XII. Description of Policies Enriched by Semantics

for Security Management 364
Félix J. García Clemente, University of Murcia, Spain
Gregorio Martínez Pérez, University of Murcia, Spain
Juan A. Botía Blaya, University of Murcia, Spain
Antonio F. Gómez Skarmeta, University of Murcia, Spain
About the Authors 391
Index 401
Preface
vi
The chapters of this book provide an excellent overview of current research
and development activities in the area of Web Semantics and ontology. They
supply an in-depth description of different issues in Web Semantics and ontol-
ogy, including modelling of Web Semantics and ontologies, using ontologies in
enterprise systems, querying and knowledge discovering of ontologies, and adopt-
ing policies and building applications. Each chapter contains a thorough study
of the topic, systematic proposed work, and a comprehensive list of references.
Following our call for chapters in 2005, we received more than 30 chapter
proposals. Each proposed chapter was carefully reviewed and eventually, 12
chapters were accepted for inclusion in this book. This book brought together
academic, researchers, and practitioners from many different countries, includ-
ing Argentina, Australia, Belgium, Canada, France, Greece, India, Italy, Spain,
and USA. Their research and industrial experience, which are reflected in their
work, will certainly allow readers to gain an in-depth knowledge of their areas
of expertise.
Intended Audience
Web Semantics and Ontology gives readers comprehensive knowledge on the
current issues of Web Semantics and ontologies. The book describes the basic
need arised from Web Semantics, the underpinning background of Web Seman-
tics, the infrastructures, languages, and tools for Web Semantics; and real-
world application domains of Web Semantics. This book is intended for indi-

vii
viduals who want to enhance their knowledge of issues relating to modelling,
adopting, querying, discovering knowledge, and building ontologies and Web
Semantics. Specifically, these individuals could include:
• General public interested in the Internet technology: General pub-
lics who are interested in the Web technology will find this book useful as
it covers current issues and practice of Web Semantics and ontology. This
book can be used as a reference book on Web Semantics and ontology.
• Information technology researchers: Researchers who are primarily
interested in current issues of Web technologies will find this book useful,
as it presents issues and state of the art of Web Semantics. The topics
that might give them particular interest include ontology, enterprise sys-
tems, modelling, knowledge discovery, queries, policies, and other issues.
• Information technology students and lecturers: The chapters in this
book are grouped into four parts to cover important issues in the area.
This will allow students and teachers in Web Semantics fields to effec-
tively use the appropriate materials as a reference or reading resources.
These categories are: (1) ontology modelling; (2) enterprise systems; (3)
retrieval and knowledge discovery; and (4) policies and applications. Since
this book covers the issues of Web Semantics and ontology comprehen-
sively, it can be used as a textbook at a graduate level.
• Web software developers: Software developers will find this book use-
ful particularly in the area of practical Web development involving OWL,
XML, RDF, metadata, and UML. The final part of this book on applica-
tions would be useful for developers in learning on how a large scale ap-
plication is built.
Prerequisites
The book as a whole is meant for anyone professionally interested in Web
Semantics and ontology and who in some way wants to gain an understanding
on how the issues in modelling and using ontologies in enterprise systems, as

well as information retrieval and knowledge discovery of Web Semantics. Each
chapter may be studied separately, or in conjunction with other chapters. As
each chapter may cover topics different from other chapters, the prerequisites
for each may vary. However, we assume the readers have at least a basic
knowledge of:
viii
• Web information systems and its applications,
• Information modelling,
• Enterprise information systems, and
• Queries and knowledge discovery.
Overview of Web Semantics
and Ontology
Over the last years there has been a steady shifting from the Internet as we
know it — unstructured, or at best, semistructured, to a more structured Web,
referred to as the Web Semantic. Web Semantics is used to denote the next
evolution step of the Web, which establishes a layer of machine understandable
data. The data is suitable for automated agents, sophisticated search engines,
and interoperability services, which provide a previously not reachable grade of
automation. The ultimate goal of Web Semantic is to allow machines the shar-
ing and exploitation of knowledge in the Web way, i.e., without central author-
ity, with few basic rules, in a scalable, adaptable, extensible manner. In other
words, Web Semantics is the key of the next generation of Web information
system, where information is given a well-defined meaning, better enabling people
and programs to work in cooperation with each other.
The emergence of Web technology has made global information sharing pos-
sible. Sharing of knowledge is motivated by Semantic Web whereby there is a
necessity to make content searching more efficient and meaningful by provid-
ing contextual and structural information about the presented contents. This
becomes possible through the establishment of an appropriate standard to de-
fine the conceptual level of a metalanguage, and such a standard is known as

an Ontology, which is described as sharable conceptualization of specific do-
main of interest in a machine-understandable format.
Web Semantics aids the efficiency of searching in the World Wide Web, by
providing more information about the presented texts. Although the applications
are many, the most common examples are intelligent search engine with data
mining capabilities, integrated decision support system applications, integrated
enterprise applications, and so forth. The structuring of information on the Web
will bring the Internet to the next era. The infrastructure to build such struc-
tured Semantic Web has been established, including the suitable language for
representation of the data (XML), translation to HTML for presentation/display
purposes (XSL), specification of metadata (RDF, XML-Schema, DTD), and
finally the establishment of an appropriate standard to define the conceptual
level of the metadata languages or the ontology (OWL, DAML-OIL).
ix
Ontologies are the backbone that keeps the Semantic Web together, because
they enforce an agreement at least on how the structure of information should
be defined. In cases where different organizations cannot agree on the same
structure, they would still use the same way of defining their structure as for-
mulated in the ontology. This will enable the development of a tool that can
translate between the different structures, thus enabling communication. While
the collection of data or information on the Internet can be seen as a static data
repository with possible regular incremental update, the user applications and
requirements that utilize the collection of data for their individual purposes will
change over time. For this reason, ontologies need to be dynamic and adaptable
to cater for the diversity of users’ needs and requirements, and the complexity
of different applications that need to be integrated.
The new era of Web Semantic has enabled users to extract semantically rel-
evant data from the Web. Web ontology plays an important role in the Semantic
Web as it defines shared uniform structures which define how Web information
is grouped and classified regardless of the implementation language or the syn-

tax used to represent the data. However, as Web ontology grows and evolves,
there are many issues to be addressed, including how it may be adopted in large
organizations, how it can be queries, how the security may be guaranteed, etc.
Organization of This Book
The book is divided into four major sections:
I. Web Semantics and Ontologies Modelling
II. Ontologies and Enterprise Systems
III. Ontologies-Based Querying and Knowledge Discovery
IV. Applications and Policies
Each section in turn is divided into several chapters:
Section I focuses on modelling of Web Semantics and ontology. This section
includes chapters on ontology extraction using views, patters, and modelling
language. Section I consists of three chapters.
Chapter I, contributed by Wouters, Rajagopalapillai, Dillon, and Rahayu,
investigates the use of materialized ontology view as an alternative efficient
version in utilizing a whole large ontology. They describe the formalism of the
materialized view for Web Semantic with conceptual and logical extensions.
x
The view provides the required conceptual and logical semantics to develop
ontological bases. They also present a schemata transformation methodology
to materialize Web Semantic view using an ontology extraction methodology
framework where materialized ontology views are instantiated.
Chapter II, presented by Kamthan and Pai, focuses on patterns, which are
refined from past experience due to recurring problems. They describe a pro-
cess of creating an ontology in the language OWL for Web Application Pat-
terns, called OWAP. The features during OWAP design, implementations and
testing are also described.
Chapter III, presented by Caliusco, Maidana, Galli, and Chiotti, introduces
contextual ontology, where an ontology is presented with its context definition.
This contextual ontology needs to be expressed in a language at run-time, par-

ticularly for the analysis and design phase of a Web domain. They present a
metamodel for modelling explicit and formal contextual ontologies to model con-
textual ontologies.
Section II concentrates on enterprise systems, covering major issues of ontol-
ogy management in large-scale enterprise systems, enterprise information sys-
tems, and semantic annotation systems for text-based document systems. This
section also consists of three chapters: Chapters IV, V, and VI.
Chapter IV, presented by Lee, Goodwin, and Akkiraju, describes their work
on developing an enterprise-scale ontology management system that provides
APIs and query languages, and scalability and performance that enterprise ap-
plications demand. They describe the design and implementation of the man-
agement system that programmatically supports the ontology needs of enter-
prise applications in a similar way a database management system supports the
data needs of applications.
Chapter V, presented by Rifaieh and Benharkat, concentrates on studying the
application of context and ontology which can serve as a formal background
for reaching a suitable enterprise information system. They focus on formalism
for contextual ontologies based combining description logics and modal logics.
This in turn helps to overcome an ontology-phobia. They also show some ex-
amples the usefulness of these contextual ontologies for resolving the semantic
sharing problems in some enterprise information systems.
Chapter VI, contributed by Reeve and Han, focuses on semantic annotation to
be a key component in Semantic Web. They propose semi-automatic semantic
annotation systems for text-based Web documents. This semantic annotation
provides services supporting annotation, including ontology and knowledge base
access and storage, information extraction, programming interfaces, and end-
user interfaces.
xi
Section III focuses on querying and knowledge discovery of ontology. It con-
sists of three chapters covering acquiring new knowledge in ontology, dynamic

knowledge discovery, and metadata and Web Semantic mining.
Chapter VII, presented by Dey and Abulaish, presents a text-mining based
ontology enhancement and query processing system. The system supports on-
tology enhancement by identifying, defining, and adding new precise and im-
precise concepts descriptions mined from text documents. They adopt a fuzzy
reasoning method for query processing.
Chapter VIII, presented by Castano, Ferrara, and Montanelli, focuses on
dynamic knowledge discovery, which is a capability of each node in a P2P or
Grid network of finding knowledge in the system about information resources
matching. They describe the models and techniques for ontology metadata man-
agement and ontology-based dynamic knowledge discovery in open distributed
systems. They also describe the HELIOS peer-based system.
Chapter IX, written by Aufaure, Le Grand, Soto, and Bennacer, presents a
state-of-the-art review of techniques covering metadata and ontologies, Se-
mantic Web information retrieval, and automatic semantic extraction. They also
describe open research areas and major current research programs in this do-
main.
Finally, Section IV presents applications and policies. This section consists of
three chapters, Chapters X, XI, and XII. These chapters present applications in
geospatial and pervasive computing, as well as policies for the security man-
agement.
Chapter X, written by Winter and Tomko, presents a review of the ways of
georeferencing in Web resources. They present a case study which investi-
gates the possibilities of translating the semantics of georeferences in Web
resources to landmarks in route directions. They also show that interpreting
goereferences in Web resources enhances the perceivable properties of de-
scribed features.
Chapter XI, presented by Tsounis, Anagnostopoulos, Hadjiethymiades, and
Karali, focuses on pervasive computing which creates an environment that
seamlessly integrate devices with computing and communication capabilities.

Since it poses an interoperability issues, they argue that the use of Web Seman-
tic technology, like ontologies, may resolve these issues.
Finally, Chapter XII, written by Clemente, Pérez, Blaya, and Skarmeta, fo-
cuses on policies. They argue that by appropriately managing policies, a system
can be continuously adjusted to accommodate variations imposed by constraints
and environmental conditions. They present an evaluation of the use of ontol-
ogy languages to represent policies for distributed systems.
xii
How to Read This Book
Each chapter in this book has a different flavor from any others due to the
nature of an edited book, although chapters within each part have a broad topic
in common. A suggested plan for a first reading would be to choose a particular
part of interest, and read the chapters in that part. For more specific seeking of
information, readers interested in ontological views and extractions, ontological
representation using OWL, ontological modelling language may read the first
three chapters. Readers interested in looking at ontological management and
adaptation in enterprise systems, as well as annotation systems may study the
chapters in the second part. Readers, who are interested in ontological queries,
metadata, knowledge discovery, and Semantic Web mining, may go directly to
the third part. Finally, those interested in applications in geospatial Semantic
Web, pervasive computing, and security management, may go directly to the
final part of this book.
Each chapter opens with an abstract that gives the summary of the chapter, an
introduction and closes with a conclusion. Following the introduction, the back-
ground and related work are often presented in order to give readers adequate
background and knowledge to enable them to understand the subject matter.
Most chapters also include an extensive list of references. This structure al-
lows a reader to understand the subject matter more thoroughly by not only
studying the topic in-depth, but also by referring to other work related to each
topic.

What Makes This Book Different?
Web Semantics is a growing area in the broader field of Web technology. A
dedicated book on important issues in Web Semantics and ontology is still diffi-
cult to find. Most books narrowly focus on one particular aspect of Web Se-
mantics, such as RDF, etc. This book is therefore different in that it covers an
extensive range of topics including ontological modelling, enterprise systems,
querying and knowledge discovery, and wide range of applications.
This book gives a good overview of important aspects in the development of
Web Semantics. The four major aspects covering ontological modelling, enter-
prise systems, Semantic Web mining, and applications, described in four parts
of this book respectively, form the comprehensive foundations of Web Seman-
tics and ontology.
The uniqueness of this book is also due to the solid mixture of both theoretical
aspects as well as practical aspects of Web Semantics and ontology develop-
xiii
ment. The application chapter presents a case study on geospatial Web Seman-
tics. Other potential applications in pervasive computing environment are also
presented. Throughout the book, languages and tools for Web Semantics and
ontology are described. These include OWL, XML, metadata, RDF, etc. Theo-
retical issues, including security management and annotation, are also covered.
Issues of adopting ontology in enterprise systems are also comprehensively
discussed.
A Closing Remark
We would like to conclude this preface by saying the this book has been com-
piled from extensive work done by the contributing authors who are research-
ers and industry practitioners in this area and who particularly have expertise in
the topic area addressed in their respective chapters. We hope that readers
benefit from the works presented in this book.
David Taniar, PhD
Johanna Wenny Rahayu, PhD

Melbourne, Australia
October 2005
Acknowledgments
xiv
The editors would like to acknowledge the help of all involved in the collation
and review process of the book, without whose support the project could not
have been satisfactorily completed.
We would like to thank all the staff at Idea Group Inc., whose contributions
throughout the whole process from inception of the initial idea to final publica-
tion have been invaluable. In particular, our thanks go to Kristin Roth, who kept
the project on schedule by continuously monitoring our progress on every stage
of the project, and to Mehdi Khosrow-Pour and Jan Travers, whose enthusiasm
initially motivated us to accept their invitations to take on this project.
We are also grateful to our employers — Monash University and La Trobe
University, for supporting this project. We acknowledge the support of the School
of Business Systems at Monash and the Department of Computer Science and
Computer Engineering at La Trobe in giving us archival server space for the
reviewing process.
A special thank goes to Mr. Eric Pardede of La Trobe University, who assisted
us in the entire process of the book: from collecting and indexing the proposals,
distributing chapters for reviews and re-reviews, constantly reminding review-
ers and authors, liaising with the publisher, to many other housekeeping duties
which are endless.
In closing, we wish to thank all of the authors for their insights and excellent
contributions to this book in addition to all those who assisted us in the review
process.
David Taniar, PhD
Johanna Wenny Rahayu, PhD
Section I
Web Semantics and

Ontologies Modelling

Ontology Extraction 1
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permission of Idea Group Inc. is prohibited.
Chapter I
Ontology Extraction
Using Views for
Semantic Web
Carlo Wouters, La Trobe University, Australia
Rajugan Rajagopalapillai, University of Technology, Sydney, Australia
Tharam S. Dillon, University of Technology, Sydney, Australia
Wenny Rahayu, La Trobe University, Australia
Abstract
The emergence of Semantic Web (SW) and the related technologies promise
to make the Web a meaningful experience. Conversely, success of SW and
its applications depends largely on utilization and interoperability of well-
formulated ontology bases in an automated heterogeneous environment.
This creates a need to investigate utilization of an (materialized) ontology
view as an alternative version of an ontology. However, high level modeling,
design and querying techniques still proves to be a challenging task for SW
paradigm, as, unlike classical database systems, ontology view definitions
and querying have to be done at high-level abstraction. In order to address
such an issue, in this chapter, we describe an abstract view formalism for
2 Wouters, Rajagopalapillai, Dillon, & Rahayu
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permission of Idea Group Inc. is prohibited.
SW (SW-view) with conceptual and logical extensions. SW-views provides
the needed conceptual and logical semantics to engineer ontology bases
using three levels of abstraction, namely (1) conceptual, (2) logical/schema

and (3) instance levels. We first provide the view model and it formal
properties including a set of conceptual operators, which enable us to do
ontology extraction at the conceptual level. Later, we provide a schemata
transformation methodology to materialize SW-views under the Ontology
Extraction Methodology (OEM) framework.
Introduction
Meaning of data is emerging as the main area of interest in the awake of
meaningful Web era, which is the Semantic Web (SW) paradigm (W3C-SW,
2005a). As envisage by Berners-Lee (1998), SW is emerging as the new medium
for the decentralized, automated global information sources for the new 21st
century information-driven economies (Aberer et al., 2004). This is highly visible
in the exponential increase of new research directions in engineering ontologies
in a wide spectrum of domains ranging from traditional enterprise data to time-
critical medical information and infectious decease databases. For such vast
ontology bases to be successful and to support autonomous computing, in a
meaningful distributed environment, the preliminary design and engineering of
such ontologies should follow strict software engineering disciplines. Further-
more, supporting technologies for ontology engineering such as data extraction,
integration and organization have be matured to provide adequate modeling and
design mechanism to build, implement and maintain successful techniques. For
such purpose, Object-Oriented (OO) paradigm seems to be an ideal choice as
it has been proven in many other complex applications and domains (Dillon &
Tan, 1993; Graham, Wills, & O’Callaghan, 2001).
OO conceptual models have the power in describing and modeling real-world
data semantics and their interrelationships in a form that is precise and
comprehensible to users (Dillon & Tan, 1993; Graham et al., 2001). But the
existing OO modeling languages (such as UML [OMG-UML™, 2003a]) provide
insufficient modeling constructs for engineering SW models and applications.
This is mainly due to lack of inherent support for semistructured schema-based
data descriptions and constraints in OO modeling languages and the shortcom-

ings of many semistructured data models in providing visual modeling and higher
levels of abstraction semantics (such as conceptual models) that are easily
understood by humans. Due to this, in the Semantic Web paradigm, most
modeling and design constructs are modeled at a lower level of abstraction,
namely schema or data description language levels.
Ontology Extraction 3
Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written
permission of Idea Group Inc. is prohibited.
Regrettably, high level modeling, design and querying techniques still proves to
be a challenging task for the SW paradigm as many requirements for such tasks
require management and organization of heterogeneous vocabularies or ontolo-
gies at higher levels of abstraction. Conversely, in SW, formulation of data
semantics are not provided by one or more fixed schema/(s), but an ontology.
Such challenges present a motivation to investigate the use of views in the SW
paradigm.
Since the introduction of view formalism in the relational data model (Date, 2003;
Elmasri & Navathe, 2004), motivation for views has changed over the last two
decades. At present view formalisms are used in Rajugan, Chang, Dillon, and
Ling (2005a): (a) user access and user access control (UAC) applications, (b)
defining user perspectives/profiles, (c) designing data perspectives, (d) dimen-
sional data modeling, (e) providing improved performance and logical abstraction
(materialized views) in data warehouse/OLAP and Web-data cache environ-
ments, (f) Web portals and profiles, and (g) Semantic Web (SW) (W3C-SW,
2005a) paradigms for sub-ontology or ontology views (Volz, Oberle, & Studer,
2003b; Wouters, Dillon, Rahayu, Chang, & Meersman, 2004b). From this list, it
is very apparent that the applications and usefulness of views are realized more
than their originally intended purpose (the 2-Es; data Extraction and Elaboration
[Figure 1]), with extensive research being carried out by both researchers and
industry to improve their design, construction and performance. Yet, the view
concept is still a data language and model dependent low-level construct

(implementation). Here we first briefly look at the history of the view mecha-
nisms available today and some of the proposals for new view mechanisms
supporting new semistructured data paradigms and SW.
Earlier we have shown that there are some important benefits in the database
area by using views. The first major benefit, being able to view information in a
different way without touching the actual structure (the adaptability aspect), is
arguably even more important for Internet applications, as most of the users
viewing the information are not the information authors, and have only read
access. In general, it can be said that the information over the Internet has many
different types of users, and it is harder to predict who these users will be while
making the data available. This prevents an author to take into account all the
users, and how they would like to view the information (i.e., what parts they
consider relevant). The first identified benefit clearly is very important to
ontologies and the Semantic Web. The second major benefit, enabling certain
types of applications using views (the extendibility aspect), is also relevant to the
Semantic Web, and once ontology views are commonplace, the same evolution
as in database area can be expected.
For the purpose of this chapter, we need to make a distinction between the
concept of abstract view definitions (addressed in this chapter) for SW and the
4 Wouters, Rajagopalapillai, Dillon, & Rahayu
Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written
permission of Idea Group Inc. is prohibited.
view definitions in SW languages such as Resource Description Framework
(RDF) (W3C-RDF, 2004) and the Ontology Web Language (OWL, previously
known as DAML+OIL) (W3C-OWL, 2002). Though expressive, SW-related
technologies and languages suffer from visual modeling techniques, fixed
models/schemas and evolving standards. In contrast, higher-level OO modeling
language standards (with added semantics to capture Ontology domain specific
constraints) are well-defined, practiced, and transparent to any underlying
model, language syntax and/or structure. They also can provide well-defined

models that can be transferred to the underlying implementation models with
ease. Therefore for the purpose of this chapter, an abstract view for SW is a
view, where its definitions are captured at a higher level of abstraction (namely,
conceptual), which in turn can be transformed, mapped, and/or materialized at
any given level of abstraction (logical, instance, etc.) in a SW-specific language
and/or model.
To address such an issue, in this chapter, we propose a view formalism for SW
(SW-view). The proposed view formalism provides: (1) conceptual and logical
semantics with extensions, (2) an OO-based design methodology to design SW
architectural constructs, and (3) an extensive set of conceptual operators
(Rajugan, Chang, Dillon, & Ling, 2005b) that can be applied in Ontology
Extraction Methodology (OEM) (Wouters et al., 2004b).
In this chapter, we present an SW-view formalism that can adapt to changing
data model and language requirements in the SW paradigm. It is independent of
data language and models, where view definitions are captured using any higher-
level modeling language such as UML or XML Semantic (XSemantic) nets
(Feng, Chang, & Dillon, 2002). Such flexibility is achieved by providing three
levels of abstraction for view definition, namely at the conceptual, logical, and
documentary levels. In addition, to support data extraction and elaboration, we
provide an extensive set of conceptual operators with corresponding restrictive
operator set for ontology extraction. The design methodology for SW-view is
based on visual OO conceptual modeling techniques discussed extensively in
Dillon and Tan (1993). Thus SW-view is a view formalism with built-in design
methodology oriented towards semistructured data models and SW.
An overview of the chapter organization is as follows: In section 2, a discussion
on view formalisms for different data models are given, followed by a brief
discussion on benefits of views and in ontologies in section 3. Section 4 provides
a detailed discussion on the view formalism for SW (SW-views), formal
definitions, modeling issues and the conceptual operators. Section 5 presents
discussion on applying SW-view formalism in the area of Ontology Extraction.

It is shown that for ontologies, the formalism can still be applied. The Ontology
Extraction Methodology uses a restricted version of the view. In section 6, a
practical example is given of how views for Semantic Web and ontology
extraction can be utilized in real-world scenarios. Especially, the automated
Ontology Extraction 5
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extraction of ontology views is used. Section 7 concludes the chapter with some
discussion on our future research direction.
Related Work
We can group the existing view models into four categories, namely: (a) classical
(or relational) views (Date, 2003; Elmasri & Navathe, 2004; Rajugan, Chang et
al., 2005a; Rajugan, Chang, Dillon, & Ling, 2005c; Wouters et al., 2004b), (b)
object-oriented view models, (c) semistructured (namely XML) view models,
and (d) view models for SW. An extensive set of literature can be found in both
academic and industry forums in relation to various view-related issues such as
(1) models, (2) design, (3) performance, (4) automation, and (5) turning/
refinement, mainly supporting the 2-Es; data Extraction and Elaboration. A
comprehensive discussion on existing view models can be also found in Rajugan,
Chang et al. (2005c). Here, we focus only on view models for semistructured
data.
Since the emergence XML (W3C-XML, 2004), the need for semistructured data
models that have to be independent of the fixed data models and data access
violates fundamental properties of classical data models. Many researchers
attempted to solve semistructured data issues by using graph-based (Zhuge &
Garcia-Molina, 1998) and/or semistructured data models (Abiteboul, Goldman,
McHugh, Vassalos, & Zhuge, 1997; Liefke & Davidson, 2000). Again, the actual
view definitions are only available at the lower level of the implementation and
not at the conceptual and/or logical level. One of the early discussions on XML
views was by Abiteboul (1999) and later more formally by Cluet et al. ( 2001).

They proposed a declarative notion of XML views. Abiteboul et al. pointed out
that a view for XML, unlike classical views, should do more than just provide
different presentation of underlying data (Abiteboul, 1999). These concepts,
which are implemented in the Xyleme project (Lucie-Xyleme, 2001), provide one
of the most comprehensive mechanisms to construct an XML view to date. But,
in relation to conceptual modeling, these view concepts provide no support.
Other view models for XML include (a) the MIX (Mediation of Information using
XML) view system (Ludaescher, Papakonstantinou, Velikhov, & Vianu, 1999),
(b) an intuitive view model for XML using Object-Relationship-Attribute model
for Semi-Structured data (ORA-SS) (Chen, Ling, & Lee, 2002). This is one of
the first view models that supports some form of abstraction above the data
language level and (c) a layered view model for XML (Rajugan, Chang et al.,
2005c), with three levels of abstraction, namely conceptual, logical, and docu-
ment level.
In related work in the Semantic Web (W3C-SW, 2005b) paradigm, some work
has been done in views for SW (Volz, Oberle, & Studer, 2003a; Volz et al.,
6 Wouters, Rajagopalapillai, Dillon, & Rahayu
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2003b), where the authors proposed a view formalism for RDF document with
support for RDF (W3C-RDF, 2004) schema (using an RDF schema supported
query language called RQL). This is one of the early works focused purely on
RDF/SW paradigm and has sufficient support for logical modeling of RDF views.
The extension of this work (and other related projects) can be found at KAON
(2004). RDF is an object-attribute-value triple, where it implies that the object
has an attribute with a value (Feng, Chang, & Dillon, 2003). It only makes
intentional semantics and not data modeling semantics. Therefore, unlike views
for XML, views for such RDF (both logical and concrete) have no tangible scope
outside its domain. In related area of research, the authors of the work propose
a logical view formalism for ontology (Wouters, Dillon, Rahayu, Chang, &

Meersman, 2004a; Wouters et al., 2004b) with limited support for conceptual
extensions, where materialized ontology views are derived from conceptual/
abstract view extensions.
Another area that is currently under development is the view formalism for SW
metalanguages such as OWL. In some SW communities, OWL is considered to
be a conceptual modeling language for modeling Ontologies, while some others
consider it to be a crossover language with rich conceptual semantics and RDF-
like schema structures (Wouters et al., 2004a). It is outside the scope of this
chapter to provide argument for or against OWL being a conceptual modeling
language. Here, we only highlight one of view formalism that is under develop-
ment for OWL, namely views for OWL in the “User Oriented Hybrid Ontology
Development Environments” (HyOntUse, 2003) project.
Views, Databases, and Ontology
The main benefits of views have evolved since it was first introduced in relational
database systems. This is mainly because the concept of views has been widely
used in various advanced applications and database systems. In this chapter, we
can categorize the benefits of views which are relevant to our proposed method
from two perspectives:
• Adaptability aspect: The concept of views provides a mechanism to
generate and present data in different structures and formats without the
necessity to redefine the underlying structure of the stored data. This
mechanism enables us to create user- or domain-oriented virtual data
subsets which are relevant to some specific requirements. The fact that the
view is only invoked on top of the stored interconnected relations means
Ontology Extraction 7
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that data integrity rules and constraints are all handled at the underlying data
level. This provides further flexibility to the created views.
• Extendibility aspect: The concept of views has enabled a number of new

and advanced applications to be built efficiently. These are normally those
applications that deal with the storage and manipulation of a large amount
of data and yet there is substantial need to analyze and view the information
in different fashions. These applications include data warehousing (Mohania,
Karlapalem, & Kambayashi, 1999; Roussopoulos, Kotidis, Labrinidis, &
Sismanis, 2001), mediators in bioinformatics databases (Do & Rahm, 2004)
and XML document repository (Chan, Dillon, & Siu, 2002; Cluet et al.,
2001). While the basic idea of views is adopted in these applications, each
of them has applied additional rules and mechanisms to make it feasible in
the new application domains.
Database is a very well-defined area, where there are clear standards of what
can and cannot be realized in a (traditional) database. Although there are
extensions (e.g., active, deductive, spatial, and temporal databases), there is still
a clear understanding of the basic principles of this area. Although the differ-
ences are many, the motivations of why databases and ontologies are used are
very similar. Both serve to structure the vast amounts of information available.
Databases transferred the unstructured text documents to structured tables and
enabled applications to use this data. A similar approach is intended for
ontologies, but then applied to the unstructured information on the Web. Because
of the characteristics of the World Wide Web, databases can not successfully
be applied to it. The major inhibitors for the database approach are:
• The Web is dynamic/ad hoc. Information is constantly changing, as well as
the intended structures. Information can be very dynamic for databases,
but the structures have to be static, and once established, should hardly
change.
• The Web is distributed. Distributed databases is not, by far, the established
area that databases is, and is still being researched. As per definition, all the
up-to-date information is spread all over the world, and this is a major
hurdle.
• The accepted standard for information, and partly responsible for the major

success of the Internet, is HTML. However, this language offers few
capabilities to structure information. Converting such documents to data-
bases would not improve the structure or the ability of the information to be
used in applications.
8 Wouters, Rajagopalapillai, Dillon, & Rahayu
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On the other hand, there is no consensus on the exact definition of an ontology,
and different approaches assign varying levels of functionality to an ontology.
For instance, OWL (W3C-OWL, 2002) lets you create instances as part of the
ontology, while the DOGMA approach (Spyns, Meersman, & Mustafa, 2002)
does not. This is just one of many differences that exist between the various
ontology standards. As a consequence, some of the elements in this chapter
depend on the chosen ontology standard, and might vary for other ontology
standards. The Ontology Extraction Methodology that is presented in Wouters,
Dillon, et al. (2002) and Wouters et al. (2004a, 2004b) addresses this problem by
providing flexible support for multiple standards. This is possible by taking a high
level approach, which can be seen in this chapter by the specification of a
conceptual view, and an extraction methodology that considers the conceptual
level. All the benefits from various ontology standards can be incorporated by
extending the methodology with optimization schemes (which are on a lower
level, i.e., standard or even language-specific level).
Views for the Semantic Web (SW-View)
The emergence of Semantic Web (SW) and the related technologies promise to
make the Web a meaningful experience. Yet, high level modeling, design, and
querying techniques still prove to be challenging tasks under the SW paradigm.
Unlike relational database views, in SW, data semantics are usually defined at
a higher level of abstraction. Therefore, a SW-view formalism should have their
definitions captured at a higher level of abstraction (Volz et al., 2003a, 2003b;
Wouters et al., 2004b) and provide some mechanisms to be able to execute over

heterogeneous data and schemas without loss of view definitions semantics.
Views in general can be considered as a special kind of transformation. Figure
1 shows a generic partitioning of any transformation into the 3 E’s: Extraction,
Elaboration, and Extension. Extraction can informally be defined as taking a part
of the original without any modifications. Elaboration is providing such an
extracted part with additional levels of detail (also referred to as interpolation).
Finally, Extension can be considered as the addition of completely new elements
(i.e., they were not present in any shape or form in the original). Although this
is an informal partitioning, it nonetheless agrees with the common vision in many
areas that use extraction.
As stated, views are a certain type of transformation. When considering Figure
1, views are purely situated in the areas of Extraction and Elaboration. Through-
out the remainder of this chapter, Extension will not be considered anymore. In
addition, a SW-view formalism should be able to deal with not just one but