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An introduction to topic maps,ontologies and published subjects
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Transcript of An introduction to topic maps,ontologies and published subjects
http://www.ontopia.net/
© 2003 Ontopia AS 1
The TAO of Topic Maps
An Introduction toTopic Maps,Ontologies, andPublished Subjects
Steve Pepper, CEO, OntopiaConvenor ISO/IEC JTC 1/SC 34/WG 3Editor XML Topic Maps<[email protected]>
http://www.ontopia.net/
© 2003 Ontopia AS 2
Who am I?
• Steve Pepper– Norway’s Head of Delegation to ISO SC34– Convenor of ISO/IEC JTC 1/SC 34/WG 3 (Information Association)– Editor of XML Topic Maps 1.0 specification (XTM)– Editor of Topic Map Constraint Language– Founder and CEO of Ontopia
• Ontopia– The Topic Map Company– Specialists in Topic Map Software and Services– Norwegian company, headquartered in Oslo
http://www.ontopia.net/
© 2003 Ontopia AS 3
What are Topic Maps?
• An international standard, approved by the ISO
• A form of knowledge representation that is optimized for information management
• A formal data model with an XML interchange syntax
• An indexing and navigation paradigm for humans
• A source of intelligent data for software agents
• A technology for exploiting ontologies
http://www.ontopia.net/
© 2003 Ontopia AS 4
Introducing the Topic Map Model
• The core concepts of Topic Maps are based on those of the back-of-book index
• The same basic concepts have been extended and generalized for use with digital information
• Envisage a 2-layer data model consisting of– a set of information resources (below), and– a “knowledge map” (above)
• This is like the division of a bookinto content and index knowledge layer
information layer
(index)
(content)
http://www.ontopia.net/
© 2003 Ontopia AS 5
(1) The Information Layer
• The lower layer contains the content– usually digital, but need not be– can be in any format or notation– can be text, graphics, video, audio, etc.
• This is like the content of the book to which theback-of-book index belongs
information layer
http://www.ontopia.net/
© 2003 Ontopia AS 6
(2) The Knowledge Layer
• The upper layer consists of topics and associations– Topics represent the subjects that the information is about
• Like the list of topics that forms a back-of-book index
– Associations represent relationships between those subjects• Like “see also” relationships in a back-of-book index
knowledge layer
composed by
born in
composed by
Puccini
Tosca
Lucca
MadameButterfly
http://www.ontopia.net/
© 2003 Ontopia AS 7
Linking the Layers Through Occurrences
• The two layers are linked together
– Occurrences are information resources that are pertinentto a given knowledge topic
– The links (or locators) arelike page numbers in aback-of-book index
Puccini
Tosca
Lucca
composed by
born in
composed by
MadameButterfly
knowledge layerinformation layer
http://www.ontopia.net/
© 2003 Ontopia AS 8
Summary of Core Topic Maps Concepts
• A pool of information or data– any type or format
• A knowledge layer, consisting of:
knowledge layerinformation layer
• Associations– expressing relationships between
knowledge topics
composed by
born in
composed by
• Occurrences– information that is relevant in some
way to a given knowledge topic
• = The TAO of Topic Maps
• Topics– a set of knowledge topics for the
domain in questionPuccini
Tosca
Lucca
MadameButterfly
http://www.ontopia.net/
© 2003 Ontopia AS 9
Topic Maps and Back-of-Book Indexes
Cavalleria Rusticana, 71, 203-204Mascagni, Pietro Cavalleria Rusticana, 71, 203-204Rustic Chivalry, see Cavalleria Rusticanasingers, 39-52 See also individual names baritone, 46 bass, 46-47 soprano, 41-42, 337 tenor, 44-45
+ other conventions
(composer)
n occurrences (and types)topics with multiple namesassociations (and types)
+ multiple indexes
• Index of names• Index of places• Index of subjects
topics (and types)
Basic concepts:
http://www.ontopia.net/
© 2003 Ontopia AS 10
Topic Maps and Ontologies
• The basic building blocks are– Topics: e.g. “Puccini”, “Lucca”, “Tosca”– Associations: e.g. “Puccini was born in Lucca”– Occurrences: e.g. “http://www.opera.net/puccini/bio.html is a biography of Puccini”
• Each of these constructs can be typed– Topic types: “composer”, “city”, “opera”– Association types: “born in”, “composed by”– Occurrence types: “biography”, “street map”, “synopsis”
• All such types are also topics (within the same topic map)– “Puccini” is a topic of type “composer” … and “composer” is also a topic
• A topic map thus contains its own ontology– (“Ontology” is here defined as the classes of things that exist in the domain…)
Demo of the Omnigator
http://www.ontopia.net/
© 2003 Ontopia AS 11
The Omnigator
A free topic map browser and debuggerOnline demo: http://www.ontopia.net/omnigator
Download: http://www.ontopia.net/download/freedownload.html
http://www.ontopia.net/
© 2003 Ontopia AS 12
The Omnigator: A Generic Topic Map Browser
• An Omnivorous Topic Map Navigator– The Omnigator will Eat Anything (provided it’s a topic map!)– Any Ontology: including your own– Just drop your own topic map into the Omnigator directory
and away you go!– The Omnigator makes “reasonable sense” out of any
“reasonably sensible” topic map
• And it's Free!– Download it from the Ontopia web site
• http://www.ontopia.net– Or view it online at
• http://www.ontopia.net/omnigator
http://www.ontopia.net/
© 2003 Ontopia AS 13
How the Omnigator Works
J2EE Web Servere.g. Tomcat
Omnigator
Ontopia TopicMap Engine
topicmap
<HTML>pages
http
server client
http://www.ontopia.net/omnigator
current topic
(multiple) names
(multiple) types
multipleoccurrences
multipleassociations
http://www.ontopia.net/
© 2003 Ontopia AS 15
With this Simple but Flexible Model You Can• Make knowledge explicit, by
– Identifying the subjects that your information is about– Expressing the relationships between those subjects
• Bridge the domains of knowledge and information, by– Describing where to find information about the subjects– Linking information about a common subject across multiple repositories
• Transcend simple categories, hierarchies, and taxonomies, by– Applying rich associative structures that capture the complexity of knowledge
• Enable implicit knowledge to be made explicit, by– Providing clearly identifiable hooks for attaching implicit knowledge
• But there’s more (of course)…
http://www.ontopia.net/
© 2003 Ontopia AS 16
Supporting Context through Scope
• Topic Maps are about representing knowledge
• Knowledge is not absolute; it has a contextual aspect
• Context sensitivity is handled through the concept of scope
• Scope makes it possible to– Cater for the subjectivity of knowledge– Express multiple viewpoints in one knowledge base– Provide personalized views for different groups of users– Track the source of knowledge during merging
• (Scopes are defined as sets of topics)
http://www.ontopia.net/
© 2003 Ontopia AS 17
How Scope Works
• Topics have “characteristics”– Its names and occurrences, and the roles it
plays in associations with other topics
• Every characteristic is valid within some context (scope), e.g.
– the name “Ruotsi” for the topicSweden in the scope “Finnish”
– a certain information occurrencein the scope “technician”
– a given association is true in thescope (according to) “Authority X”
name
occurrence
association roleassociation role
name
occurrence
association role
nameTT
name
occurrence
association role
nameT
Filtering by scope
http://www.ontopia.net/
© 2003 Ontopia AS 18
Applications of Scope
• Multiple world views– Reality is ambiguous and knowledge has a subjective dimension– Scope allows the expression of multiple perspectives in a single Topic Map
• Contextual knowledge– Some knowledge is only valid in a certain context, and not valid otherwise– Scope enables the expression of contextual validity
• Traceable knowledge aggregation– When the source of knowledge is as important as the knowledge itself:– Scope allows retention of knowledge about the source of knowledge
• Personalized knowledge– Different users have different knowledge requirements– Scope permits personalization based on personal references, skill levels,
security clearance, etc.
Demo of scope and filtering in the Omnigator
http://www.ontopia.net/
© 2003 Ontopia AS 19
How Topic Maps Improve Access to Information• Intuitive navigational interfaces for humans
– The topic/association layer mirrors the way people think
• Powerful semantic queries for applications– A formal underlying data structure– Demo of querying in the Omnigator
• Customized views based on individual requirements– Personalization based on scope
• Information aggregation “sans frontiers”– Topic Maps can be merged automatically…– Demo of merging in the Omnigator
http://www.ontopia.net/
© 2003 Ontopia AS 20
Principles of Merging in Topic Maps
• In Topic Maps, every topic represents some subject
• The collocation objective requires exactly one topic per subject– When two topic maps are merged, topics that represent the
same subject should be merged to a single topic– When two topics are merged, the resulting topic has the
union of the characteristics of the two original topics
name
occurrence
association role
T
association role
name
occurrence
association role
name
A second topic (in another topic map) “about” the same subject
TMerge the two topics together...Merge the two topics together...
...and the resulting topic has the unionof the original characteristics
name
occurrence
association role
nameT
Det uunngåelige Ibsen-eksempelet
SNL
SNL
SNL
SNL
Skienkom-mune
CapLex
CapLex
NBL
Henrik Ibsen
Hedda Gabler
Skien
Et dukkehjemA doll’s house
skrev
født i
skrev
“virkelighet”
emnekart
informasjon
kunnskap
Ibsen-senter
Ibsen-senter
Ibsen-senter
Ibsen-senter
Ibsen-senter
Ibsen-senter
Et dukkehjemHelmerHelmer
Dr. RankDr. RankFru LindeFru Linde
KrogstadKrogstadNoraNora
http://www.ontopia.net/
© 2003 Ontopia AS 22
Applications of Merging
• Information integration– Information that spans multiple repositories can be merged to provide a unified view of
the whole
• Knowledge sharing across the organization– Knowledge captured in one part of an organization can be made available to the whole
organization
• Distributed knowledge management– There is no need to centralize knowledge management in order to make it sharable
• Knowledge sharing between organizations– Information and knowledge can be shared without enforcing a common vocabulary
http://www.ontopia.net/
© 2003 Ontopia AS 23
Integrating Information Across Systems
• Topic Maps are designed for ease of merging!– Multiple Topic Maps can be created from many different repositories of
information ... and then merged to provide a unified view of the whole
• Typical Applications:– Integration of hitherto disconnected “islands” of information within an enterprise– Federation of knowledge
from multiple sources
• Advantages:– Consolidated access to
all related information– Does not require
migration of existingcontent
KnowledgeSpace
InformationSpace
Order2
CustomerA
Order1
CustomerB
ProductX
ProductZ
SkillQ
ProductY
owns
orders
orders
contains
contains
containsintegrates
integrates
requires
Customerdatabase
Orderdatabase
Productdatabase
Skillsdatabase
Customerdatabase
http://www.ontopia.net/
© 2003 Ontopia AS 24
What Makes Merging Possible?
• NOT the use of names, which are notoriously unreliable– Names are not unambiguous
• (the homonym problem)– Many topics have multiple names
• (the synonym problem)
• Reliable knowledge aggregation is only possible through the use of unique global identifiers
• The issue of identification of subjects is crucial– If subjects have unique identifiers, people can be free to use whatever
names they like – and machines can still aggregate information
http://www.ontopia.net/
© 2003 Ontopia AS 25
COMPUTERDOMAIN
The Crucial Concept of Subject Identification• Topics exist in order to allow
us to discourse about subjects
• It is crucially important to be able to establish exactly which subject a topic represents, i.e. to establish its subject identity
– Without the ability to know when applications are talking about the same thing, there can be no interoperability
• The most prevalent method of establishing identity in today’s networked environments is to use URIs
“REALITY”
knowledge layerinformation layer
composed by
born in
composed by
Puccini
Tosca
Lucca
MadameButterfly
http://www.ontopia.net/
© 2003 Ontopia AS 26
Using URIs to Identify Resources
http://www.ontopia.net/
© 2003 Ontopia AS 27
Addressable and Non-addressable Subjects
• URIs are the addresses of resources
• They work fine when subject is a resource (e.g. a document)– It exists somewhere within the computer system, has a location, and can
therefore be “addressed”• For example, this presentation might be located at
http://www.ontopia.net/tutorials/tm-intro.ppt– The address of an addressable subject is sufficient to unambiguo establish the
subject’s identity– This is called the subject address
• But most subjects are not information resources– Puccini, Lucca, Tosca, Madame Butterfly, love, darkness, French, …– These all exist outside the computer domain and cannot be addressed directly
http://www.ontopia.net/
© 2003 Ontopia AS 28
Life, the Universe and Everything
The Computer Domain
The Topic Map Domain
Subject Indicators
• The identity of non-addressable subjects is established indirectly
– Through an information resource (like a definition or a picture) that provides some kind of indication of the subject’s identity to a human
– Such a resource is called asubject indicator
– A topic may have multiple subject indicators
• Because it is a resource, a subject indicator has an address, even though the subject that it is indicating does not
– Computers can use the address of the subject indicator to establish identity
– These are called subject identifiers– Subject indicators and subject identifiers
are the two sides of the human-computer dichotomy
subject
Giacomo Puccini, Italian composer, b. Lucca 22nd Dec 1858, d. Brussels, 29th Nov 1924. Best known for his operas, of which Tosca is the most . . .
subject indicator
Puccini
http://p
si.ontopia.
net/o
pera/pucc
ini.htm
l
subject identifier
topichttp://
www.ontopia.net/© 2002 Ontopia AS
http://www.ontopia.net/
© 2003 Ontopia AS 29
Published Subjects
• A subject indicator that has been made available for use outside one particular application is called a published subject indicator (PSI)
– Anyone can publish PSI sets– Adoption of PSI sets will be an evolutionary process that will lead to greater and
greater interoperability – between topic map applications, between topic maps and RDF, and across the Semantic Web in general
– Publishers and users of ontologies may be among the greatest beneficiaries
• OASIS technical committees– pubsubj: http://www.oasis-open.org/committees/tm-pubsubj/
• Guidelines for publishing PSI sets– geolang: http://www.oasis-open.org/committees/geolang/
• A PSI set for geographical and language subjects• Based on existing standards (e.g. ISO 639, ISO 3166)
– xmlvoc: http://www.oasis-open.org/committees/xmlvoc/• A PSI set for an ontology of XML and related standards
http://www.ontopia.net/
© 2003 Ontopia AS 30
Using URIs to Identify Arbitrary Subjects
http://www.ontopia.net/
© 2003 Ontopia AS 31
Using URIs to Identify Resources
http://www.ontopia.net/
© 2003 Ontopia AS 32
A Plea to Ontology Developers
• Make them publicly available!
• Define URIs as unique identifiers for the concepts in your ontologies – including the relationship types
– http://psi.fao.org/disease/#bse
• Follow the Recommendations of the OASIS Published Subjects TC:– Make sure they resolve to human-readable resources– Guarantee their stability
• This will allow human users to use different terminology– Bovine Spongiform Encephalopathy (?), BSE– Mad Cow Disease– Kugalskap, La vache folle, etc.
• And enable interoperability and reuse across applications:– Topic Maps, RDF, DAML+OIL, OWL, KIF, XML, etc.
http://www.ontopia.net/
© 2003 Ontopia AS 33
Topic Maps for Machine Agents
• A formal data structure suitable for data processing
• Support for rich semantic queries
• High degree of built-in semantics simplifies application development
• Published Subjects enable widespread and spontaneous knowledge interchange
• International standard interchange syntax
• Potential for wide adoption means more data for agents
http://www.ontopia.net/
© 2003 Ontopia AS 34
Topic Maps for Human Agents
• A way of representing knowledge that corresponds to how humans think about the world
– Organized around subjects not resources– Direct support for context sensitivity
• A level of built-in semantics that makes the model easy to understand– Distinguishes between names, occurrences and associations– Privileges the class-instance relationship
• Associative model matches how the brain works– Typed associations provide a rich and intuitive navigational interface
http://www.ontopia.net/
© 2003 Ontopia AS 35
Topic Map-Driven Knowledge Portals
• Let the index drive the presentation!– The Topic Map structure governs the application – and the knowledge
• Users navigate intuitively from topic to topic– Having found the appropriate topic, they
• immediately see all recorded explicit knowledge• can dip down into information resources to “extract” implicit knowledge
• Publisher benefits:– Easier content maintenance (simply update the Topic Map)– Easier link maintenance (links are in separate layer, not in content)– New portals easy to derive from same content
• User benefits:– Shorter click-through– Easier, more intuitive navigation mirrors associative way of thinking– Far greater structural consistency means less confusion
Demo of the OperaMap portalhttp://www.ontopia.net/operamap
http://www.ontopia.net/
© 2003 Ontopia AS 36
For More Information
• “Getting Started with Topic Maps”
• Ontopia web site– http://www.ontopia.net
• /me– [email protected]
• Finally– Ontopia is the world’s leading Topic Map company– We are interested in participating in EU projects– Please contact me for more details