http:// © 2003 ontopia as 1 iso 13250:2002 – topic maps an international standard knowledge...

http://www.ontopia.net/

© 2003 Ontopia AS 1

ISO 13250:2002 – Topic Maps

An International Standard

Knowledge Representation for

Humans and Agents

Steve Pepper, CEO, Ontopia

Convenor ISO/IEC JTC 1/SC 34/WG 3

Editor XML Topic Maps

<[email protected]>



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– State-of-the-Art Topic Map software vendor

• Middleware (core Topic Map engine, J2EE application frameworks)

– The Oracle of Topic Maps

– Norwegian company, headquartered in Oslo

– Potential industry partner in openNet and FP6 projects



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



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)



(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



(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



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 layer

information layer



Summary of Core Topic Maps Concepts

• A pool of information or data– any type or format

• A knowledge layer, consisting of:

knowledge layer

information 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



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…)

• Constraints on the ontology are defined separately– Topic Map Constraint Language (ISO 19756) will provide a standard way to do this– It is likely to be based on, or compatible with, DAML+OIL and/or OWL



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 (additional) 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

• Provide easier access to information, through– Intuitive navigational interfaces– Powerful semantic queries

Demo of the OmnigatorA free topic map browser from http://www.ontopia.net/omnigator



The Omnigator

A free topic map browser

Online demo: http://www.ontopia.net/omnigator

Download: http://www.ontopia.net/download/freedownload.html



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 directoryand 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

• Built using Ontopia’s flagship product– The Ontopia Knowledge Suite (OKS)

– A complete Java toolkit for building topic map applications

– Academic licenses available from [email protected]



The Omnigator: A Generic Topic Map Browser

• An Omnivorous Topic Map Navigator– The Omnigator will Eat Anything (provided it’s a topic map!)

– Any syntax: XTM, HyTM, LTM

– Any ontology: including your own

– Just drop your own topic map into the Omnigator directoryand 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



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/omnigator



Topic Map Query Language

• ISO/IEC 18048 TMQL– Intended to simplify application development

– Used to extract information and modify TMs

• A requirements document exists

• Various proposals have been put forward– One of these will be chosen as the basis of TMQL this spring

• Ontopia has developed tolog– tolog also supports inferencing

Demo of querying in the Omnigator



Topic Map Constraint Language

• ISO/IEC 19756 TMCL

• Used to define constraints on topic maps– “all persons must be born somewhere”

– “a person may have died somewhere”

– “all persons must have a date of birth occurrence, which must contain a date”

– “email occurrences are unique”

• Ontopia has developed OSL– Ontopia Schema Language

• TMCL may be based on OWL (Web Ontology Language)

Demo of OSL in the Omnigator



Advanced Concepts in Topic Maps

Subject Identity

Published Subjects

Scope

Reification



COMPUTERDOMAIN

The Crucial Concept of Subject Identity

• 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

• How identity is established depends on whether the subject is an information resource or something else

• Most subjects are not resources and therefore do not have “addresses”

“REALITY”

knowledge layer

information layer

composed by

born in

composed by

Puccini

Tosca

Lucca

MadameButterfly



Addressable and Non-addressable Subjects

• Sometimes the subject is an information 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 unequivocably 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



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://

psi.o

ntopia

.net

/oper

a/pucc

ini.h

tml

subject identifier

topichttp://

www.ontopia.net/© 2002 Ontopia AS



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

– Agent Technologies 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



Topic Map Merging

• The concept of Subject Identity makes it possible toautomatically merge topic maps

– When two topic maps are merged, topics that represent thesame subject should be merged to a single topic

– When two topics are merged, the resulting topic has theunion 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

name

T



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

Demo of merging in the Omnigator



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



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 “Allemagne” for the topicGermany in the scope “French”

– the name “composer of” (for the association type “composed by”) in the scope “composer”

– a certain information occurrencein the scope “technician”

– a given association is true in thescope (according to) “Authority X”

name

occurrence

association role

association role

name

occurrence

association role

name

TTname

occurrence

association role

name

T

Filtering by scope



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



Topic Maps for Humans

• 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



Topic Maps for 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



For More Information

• “Getting Started with Topic Maps”– In your handouts

• Ontopia web site– http://www.ontopia.net

• /me– [email protected]

• Finally– Ontopia is the world’s leading Topic Map company

– Our Topic Map Engine can complement your Agent Technologies

– Consider us as industry partners in openNet and other FP6 projects

– Norway is a member of the EEA (not the EU)

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