XML Topic Maps: Creating and Using Topic Maps for the Web

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Overview

The explosive growth of the World Wide Web is fueling the need for a new generation of technologies for managing information flow, data, and knowledge. This developer's overview and how-to book provides a complete introduction and application guide to the world of topic maps, a powerful new means of navigating the World Wide Web's vast sea of information.

With contributed chapters written by today's leading topic map experts, XML Topic Maps is designed to be a "living document" for managing information across the Web's interconnected resources. The book begins with a broad introduction and a tutorial on topic maps and XTM technology. The focus then shifts to strategies for creating and deploying the technology. Throughout, the latest theoretical perspectives are offered, alongside discussions of the challenges developers will face as the Web continues to evolve. Looking forward, the book's concluding chapters provide a road map to the future of topic map technology and the Semantic Web in general.

Specific subjects explored in detail include:

  • Topic mapping and the XTM specification
  • Using XML Topic Maps to build knowledge repositories
  • Knowledge Representation, ontological engineering, and topic maps
  • Transforming an XTM document into a Web page
  • Creating enterprise Web sites with topic maps and XSLT
  • Open source topic map software
  • XTM, RDF, and topic maps
  • Semantic networks and knowledge organization
  • Using topic maps in education
  • Topic maps, pedagogy, and future perspectives

Featuring the latest perspectives from today's leading topic map experts, XML Topic Maps provides the tools, techniques, and resources necessary to plot the changing course of information management across the World Wide Web.

0201749602B08282002

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Editorial Reviews

From The Critics
The first volume of the projected series Open Knowledge Systems explains how programmers can apply topic maps to knowledge representation. Veterans of the technology discuss such aspects as the paradigm, the quest for global knowledge interchange, specification, and creating and maintaining enterprise web sites. Annotation c. Book News, Inc., Portland, OR
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Product Details

  • ISBN-13: 9780201749601
  • Publisher: Addison-Wesley
  • Publication date: 7/16/2002
  • Edition description: New Edition
  • Pages: 605
  • Product dimensions: 7.24 (w) x 9.05 (h) x 1.41 (d)

Meet the Author

Jack Park is a founding member of the XTM Topic Maps in XML authoring group. He was a senior scientist with VerticalNet Solutions in Palo Alto, CA, where he was actively engaged in the development of knowledge representation systems in support of online B2B communities. His discovery program entitled The Scholar's Companion(R) has been used to develop knowledge bases in advanced research on hyperbaric immunology. He is the lead developer of an XML Topic Maps-based knowledge management system on the Web at http://nexist.sourceforge.net, and is active in the development of Open Hyperdocument Systems technology with the Bootstrap Alliance.

Sam Hunting is the principal of eTopicality, Inc., a consultancy whose service offerings include topic maps, content analysis, and DTD development. He was a founding member of TopicMaps.Org, which developed the XML Topic Maps (XTM) specification. He is a coauthor of the XTM 1.0 DTD and a cofounder of the GooseWorks project for creating open source topic map tools. He can be reached at http://www.etopicality.com.

0201749602AB08282002

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Read an Excerpt

In a former life, I built microprocessor-based data acquisition systems, originally for locating and monitoring wind and solar energy systems. I suppose it is fair to say that I have long been involved in roaming solution space. Along the way, farmers, on whose land the energy systems were often situated, discovered that my monitoring tools helped them form better predictions of fruit frost, irrigation needs, and pesticide needs. My program, which ran on an Apple II computer that had telephone access to the distributed monitoring stations, printed out large piles of data. Epiphany happened on the day that a manager of one of those monitoring systems came to me and asked, "What else is this data good for?" That was the day I entered the field of artificial intelligence, looking for ways to organize all that data and mine it for new knowledge.

A recent discussion on National Public Radio focused on the nature and future of literature. Listening to that conversation while navigating the perils of Palo Alto traffic, I heard two comments that I shall paraphrase, with emphasis placed according to my own whims, as follows: In the past, we turned to the great works of literature to ponder what is life. Today, we turn to the great works of science to ponder the same issues.

In some sense, the message I pulled out of that is that we (the really big we) tend to appeal to science and technology to find comfort and solutions to our daily needs. In that same sense, I found justification for this book and the vision I had when the book was conceived. Make no mistake here—I already had plenty of justification for the vision and the book. As is often pontificated by many, we are engulfed in a kind of information overload that threatens to choke off our ability to solve major problems that face all of humanity.

No, the vision is not an expression of doom and gloom. Rather, it is an expression of my own deep and optimistic belief that it is through education, through an enriched human intellect, that solutions will be found, or at least, the solution space will become a more productive environment in which to operate. The vision expressed here is well grounded in the need to organize and mine data, all part of the solution space.

While walking along a corridor at an

This book is the first in that series, flying under the moniker Open Knowledge Systems. By using the word open, I am saying that the series is about making the tools and information required to operate in solution space completely open and available to all who would participate. Open implies that each book in the series intends to include an Open Source Software project, one that enables all readers to immediately "play in the sandbox" and, hopefully, go beyond by extending the software and contributing that new experience to solution space.

This book is about topic maps, particularly topic maps implemented in the XTM Version 1.0 specification format, as conceived by the XTM Authoring Group, which was started by an experienced group of individuals along with the vision and guidance of Steve Newcomb and Michel Biezunski, both contributing authors for this book. As with many new technologies, the XTM specification is, in most regards, not yet complete. In fact, a standard like XTM can never be complete simply because such standards must coevolve with the environment in which they are applied. In the same vein, a book such as this cannot be a coherent work simply because much of what is evolving now is subject to differing opinions, views, and so forth.

There are a few assumptions made by all of the authors who contributed to this book. Mostly, the assumptions presume some minimal familiarity with Extensible Markup Language (

Because of my view that solution space itself is coevolving along with the participants in that space, I have adopted an editorial management style that I suspect should be explained. My style is based on the understanding that I am combining contributions from many different individuals, each with a potentially different worldview and each with a different writing style. The content focus of this book is, of course, on topic maps, but I believe that it is not necessary to force a coherent worldview on the different authors—it is my hope that readers and, indeed, solution space will profit by way of exposure to differing views and opinions. There will, by the very nature of this policy, be controversy. Indeed, we are exploring the vast universe of discourse on the topic of knowledge, and there exists plenty of controversy just in that sandbox alone.

There is also the possibility of overlap. Some chapters are likely to offer the same or similar (or even differing) points of view on the same point. Case in point: knowledge representation. This book has several chapters on that topic: one on ontological engineering, one on knowledge representation, and one on knowledge organization. Two chapters talk in some detail about semantic networks, and other chapters discuss how people learn. It's awfully easy to see just how these can overlap, and they do. My management style has been that which falls out of research in chaos theory: use the least amount of central management, and let the authors sort it out for themselves. History will tell us whether this approach works.

0201749602P08282002

Read More Show Less

Table of Contents

Foreword
Preface
Acknowledgments
Contributors
Ch. 1 Let There Be Light 1
Ch. 2 Introduction to the Topic Maps Paradigm 17
Ch. 3 A Perspective on the Quest for Global Knowledge Interchange 31
Ch. 4 The Rise and Rise of Topic Maps 51
Ch. 5 Topic Maps from Representation to Identity: Conversation, Names, and Published Subject Indicators 67
Ch. 6 How to Start Topic Mapping Right Away with the XTM Specification 81
Ch. 7 Knowledge Representation, Ontological Engineering, and Topic Maps 103
Ch. 8 Topic Maps in the Life Sciences 149
Ch. 9 Creating and Maintaining Enterprise Web Sites with Topic Maps and XSLT 167
Ch. 10 Open Source Topic Map Software 199
Seman Text 204
XTM Programming with TM4J 211
Nexist Topic Map Testbed 244
GooseWorks Toolkit 260
Ch. 11 Topic Map Visualization 267
Ch. 12 Topic Maps and RDF 283
Ch. 13 Topic Maps and Semantic Networks 327
Ch. 14 Topic Map Fundamentals for Knowledge Representation 357
Ch. 15 Topic Maps in Knowledge Organization 383
Ch. 16 Prediction: A Profound Paradigm Shift 477
Ch. 17 Topic Maps, the Semantic Web, and Education 507
Glossary 531
App. A Tomatoes Topic Map 543
App. B Topic Map for Chapter 9 547
App. C XSLT Style Sheet for Chapter 9 563
App. D Genealogical Topic Map 569
Index 585
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Preface

In a former life, I built microprocessor-based data acquisition systems, originally for locating and monitoring wind and solar energy systems. I suppose it is fair to say that I have long been involved in roaming solution space. Along the way, farmers, on whose land the energy systems were often situated, discovered that my monitoring tools helped them form better predictions of fruit frost, irrigation needs, and pesticide needs. My program, which ran on an Apple II computer that had telephone access to the distributed monitoring stations, printed out large piles of data. Epiphany happened on the day that a manager of one of those monitoring systems came to me and asked, "What else is this data good for?" That was the day I entered the field of artificial intelligence, looking for ways to organize all that data and mine it for new knowledge.

A recent discussion on National Public Radio focused on the nature and future of literature. Listening to that conversation while navigating the perils of Palo Alto traffic, I heard two comments that I shall paraphrase, with emphasis placed according to my own whims, as follows: In the past, we turned to the great works of literature to ponder what is life. Today, we turn to the great works of science to ponder the same issues.

In some sense, the message I pulled out of that is that we (the really big we) tend to appeal to science and technology to find comfort and solutions to our daily needs. In that same sense, I found justification for this book and the vision I had when the book was conceived. Make no mistake here--I already had plenty of justification for the vision and the book. As is often pontificated by many, we are engulfed in a kind of information overload that threatens to choke off our ability to solve major problems that face all of humanity.

No, the vision is not an expression of doom and gloom. Rather, it is an expression of my own deep and optimistic belief that it is through education, through an enriched human intellect, that solutions will be found, or at least, the solution space will become a more productive environment in which to operate. The vision expressed here is well grounded in the need to organize and mine data, all part of the solution space.

While walking along a corridor at an XML conference in San Jose early in the year 2000, I noticed a sign that said "Topic Maps," with an arrow pointing to the right. I proceeded immediately to execute a personal "column right" command, entered a room, and met Steve Newcomb. The rest all makes sense. While in Paris later that year, I saw the need to take the XTM technology to the public. This book was then conceived at XML 2000 in Paris, and several authors signed on immediately. This book came with a larger vision than simply taking XTM to the public. I saw topic maps as an important tool in solution space. The vision included much more; topic maps are just one of many tools in that space. I wanted to start a book series, one that is thematically associated with my view of solution space.

This book is the first in that series, flying under the moniker Open Knowledge Systems. By using the word open, I am saying that the series is about making the tools and information required to operate in solution space completely open and available to all who would participate. Open implies that each book in the series intends to include an Open Source Software project, one that enables all readers to immediately "play in the sandbox" and, hopefully, go beyond by extending the software and contributing that new experience to solution space.

This book is about topic maps, particularly topic maps implemented in the XTM Version 1.0 specification format, as conceived by the XTM Authoring Group, which was started by an experienced group of individuals along with the vision and guidance of Steve Newcomb and Michel Biezunski, both contributing authors for this book. As with many new technologies, the XTM specification is, in most regards, not yet complete. In fact, a standard like XTM can never be complete simply because such standards must coevolve with the environment in which they are applied. In the same vein, a book such as this cannot be a coherent work simply because much of what is evolving now is subject to differing opinions, views, and so forth.

There are a few assumptions made by all of the authors who contributed to this book. Mostly, the assumptions presume some minimal familiarity with Extensible Markup Language (XML), Extensible Style Language (XSL and XSLT), and Resource Description Framework (RDF). Please keep in mind that the book presents many Web site references. Web sites occasionally disappear. While the links presented were tested during the writing phase and again during final manuscript editing, do not be surprised if some of them fail to remain in service. Since this book will remain a living document on the Web, we hope to keep all links up-to-date on the book's Web site.

Because of my view that solution space itself is coevolving along with the participants in that space, I have adopted an editorial management style that I suspect should be explained. My style is based on the understanding that I am combining contributions from many different individuals, each with a potentially different worldview and each with a different writing style. The content focus of this book is, of course, on topic maps, but I believe that it is not necessary to force a coherent worldview on the different authors--it is my hope that readers and, indeed, solution space will profit by way of exposure to differing views and opinions. There will, by the very nature of this policy, be controversy. Indeed, we are exploring the vast universe of discourse on the topic of knowledge, and there exists plenty of controversy just in that sandbox alone.

There is also the possibility of overlap. Some chapters are likely to offer the same or similar (or even differing) points of view on the same point. Case in point: knowledge representation. This book has several chapters on that topic: one on ontological engineering, one on knowledge representation, and one on knowledge organization. Two chapters talk in some detail about semantic networks, and other chapters discuss how people learn. It's awfully easy to see just how these can overlap, and they do. My management style has been that which falls out of research in chaos theory: use the least amount of central management, and let the authors sort it out for themselves. History will tell us whether this approach works.

0201749602P08282002

Read More Show Less

Introduction

A human being is part of a whole, called by us the "Universe," a part limited in time and space. He experiences himself, his thoughts and feelings, as something separated from the rest—a kind of optical delusion of his consciousness. This delusion is a kind of prison for us, restricting us to our personal desires and to affection for a few persons nearest us. Our task must be to free ourselves from this prison by widening our circles of compassion to embrace all living creatures and the whole of nature in its beauty. Albert Einstein, What I Believe, 1930

In a former life, I built microprocessor-based data acquisition systems, originally for locating and monitoring wind and solar energy systems. I suppose it is fair to say that I have long been involved in roaming solution space. Along the way, farmers, on whose land the energy systems were often situated, discovered that my monitoring tools would help them form better predictions of fruit frost, irrigation needs, and pesticide needs. My program, which ran on an Apple II that had telephone access to the distributed monitoring stations, printed out large piles of data. Epiphany happened on the day that a manager of one of those monitoring systems came to me and asked "What else is this data good for?" That was the day I entered the field of artificial intelligence, looking for ways to organize all that data and mine it for new knowledge.

A recent issue of a National Public Radio discussion focused on the nature and future of literature. Listening to that discussion while navigating the perils of Palo Alto traffic, I heard two comments that I shall paraphrase, with emphasis placed according to my ownwhims, as follows:

In the past, we turned to the great works of literature to ponder what is life. Today, we turn to the great works of science to ponder the same issues.

In some sense, the message I pulled out of that is that we (thatUs the really big we) tend to appeal to science and technology to find comfort and solutions to our daily needs. In that same sense, I found justification for this book and the vision I had when the book was conceived. Make no mistake here, I already had plenty of justification for the vision and the book; as is often pontificated by many, we are engulfed in a kind of information overload that threatens to choke off our ability to solve major problems that face all of humanity.

No, the vision is not an expression of doom and gloom. Rather, it is an expression of my own deep and optimistic belief that it is through education, through an enriched human intellect that solutions will be found, or at least, the solution space will become a more productive environment in which to operate. The vision expressed here is well grounded in the need to organize and mine data, all part of the solution space.

While walking along a corridor at an XML conference in San Jose early in the year 2000, I noticed a sign that said Topic Maps, with an arrow pointing to the right. I proceeded immediately to execute a personal "column right" command, entered a room, and met Steve Newcomb. The rest all makes sense; while in Paris later that year, I saw the need to take the XTM technology to the public. This book was then conceived at XML2000 in Paris, and several authors signed on immediately. This book came with a larger vision than simply taking XTM to the public. I saw topic maps as an important tool in solution space. The vision included much more; topic maps are just one of many tools in that space. I wanted to start a book series, one that is thematically associated with my view of solution space.

This book is the first in a book series, flying under the moniker Open Knowledge Systems. By using the word open, I am saying that the series is about making the tools and information required to operate in solution space completely open and available to all who would participate. "Open" implies that each book in the series intends to include an Open Source Software project, one that enables all readers to immediately "play in the sandbox" and, hopefully, go beyond by extending the software and contributing that new experience to solution space.

Each contribution to the Open Knowledge Systems series is intended to be a living document, meaning that each work will be available at a web site, the entire content of which will be browsable and supported with an online forum such that topics discussed in the books can be further discussed online.

This book is about Topic Maps, particularly Topic Maps implemented in the XTM Version 1.0 Standard format, as conceived by the XTM Authoring Group, which was started by an experienced group of individuals along with the vision and guidance of Steven Newcomb and Michel Biezunski, both contributing authors in this book. As with many new technologies, the XTM standard is, in most regards, not yet complete. In fact, a standard like XTM can never be complete simply because such standards must co-evolve with the environment in which they are applied. In the same vein, a book such as this cannot be a coherent work, simply because much of what is evolving now is subject to differing opinions, views, and so forth.

Because of my view that solution space, itself, is co-evolving along with the participants in that space, I have adopted an editorial management style that I suspect should be explained. My style is based on the understanding that I am combining contributions from many different individuals, each with a potentially different worldview, and each with a different writing style. The content focus of this book is, of course, on Topic Maps, but I believe that it is not necessary to force a coherent worldview on the different authors; it is my hope that readers, and, indeed, solution space will profit by way of exposure to differing views and opinions. There will, by the very nature of this policy, be controversy. Indeed, we are exploring the vast universe of discourse on the topic of knowledge, and there exists plenty of controversy just in that sand box alone.

There is also the possibility of overlap. Some chapters are likely to offer the same or similar, or even differing points of view on the same point. Case in point: knowledge representation. We have several chapters, one on Ontological Engineering, one on Knowledge Representation, and one on Knowledge Organization. Two talk in some detail about semantic networks, and others go heavily into how people learn. ItUs awfully easy to see just how these can overlap, and they do. My management style has been that which falls out of research in Chaos: use the least amount of central management; let the authors sort it out for themselves. History will tell us if this approach works.



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  • Anonymous

    Posted October 10, 2002

    XML Topic Maps - the next level above XML?

    Since Tim Berners-Lee wrote of the Semantic Web several years ago, there has been speculation about how we might embed meaning within Web pages, as opposed to merely displaying content. To answer this, XML offers the separation of content from display. From its user definable tags, different user communities can define their own sets of tags and associate meaning with those. XML offers the infrastructure. But it is still fairly low level. Assembler language, as it were, compared to more powerful languages like C or Java. So if XML is like an assembler, what is the analog of C? This book puts forward XTM, XML Topic Maps, as the answer. It consists of 17 chapters by different authors, outlining various aspects of XTM. The chapters can be divided into two types. One type has nitty gritty explanations, replete with examples of XTM written in XML. If you are a programmer, these chapters are for you. There are web sites listed with XTM definitions that you can incorporate into your XTM, just like using standard namespaces available on the web in normal XML. The other chapters deal with the much deeper and harder problem of how XTM may be used for Knowledge Organisation and Knowledge Representation. They are high level and abstruse, edging up to the issues of semiotics and artificial intelligence. As a side note: In the XTM examples and implementations given, I was surprised to see no mention of altavista's graphical representation of search results, circa 1998. This was not in XTM, but it conveyed the flavour. What happened was that if you searched for, say, 'tornado', the results would appear as a graph. The nodes would be the main keywords in the documents containing 'tornado'. Nodes would be connected to each other if documents contained both those words. In this case, one might see two non intersecting clusters - one related to weather patterns, and the other to jet planes. By clicking on a node, you could expand it into finer grained graphs. It complements this book, whose main thrust is in manually describing XML documents in an XTM format, because it could achieve much the same visual results, but derived automatically from arbitrary web pages.

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