topic maps for the three kingdoms: the many applications of topic maps

Topic Mapsfor the Three KingdomsThe Many Applications ofTopic Maps

AToMS, Seoul, June 2006Steve PepperChief Strategy Officer, OntopiaConvenor, SC34/WG3Editor, XML Topic Maps<[email protected]>

http://www.ontopia.net/© 2006 Ontopia AS

What I Will Talk About• What are the Three Kingdoms?• Advantages of Topic Maps• Major Application Areas of Topic Maps

– Semantic Indexing– Information Integration– Knowledge Management & eLearning

• National Knowledge Base for Korea• (Topic Maps and the Semantic Web)• Conclusion


The Three Kingdoms1. Silla, Goguryeo, Paekche:

the Three Kingdoms of early Korean history– Topic Maps have something to offer for everyone

in Korea: A National Knowledge Base for Koreawould be a wonderful thing

2. Industry, Public Sector, Education & Research– Topic Maps can be applied across every sector)

3. Semantic Indexing, Information Integration,Knowledge Management/eLearning– Topic Maps cover a wide variety of application areas

4. Norway, Netherlands, and ... USA– Well, USA is not a kingdom, but it could have been…


Key Advantages of Topic Maps

• Topic Maps provides a subject-centric, associative model for representing knowledge

• The basic ideas are not new– They are familiar from library science, cognitive psychology,

artificial intelligence, etc.

• But the key advantages are new– ISO standard – vendor independence, longevity– Formal data model – machine processable– Interchange syntax – use across multiple systems

• Let’s see how to apply these advantages...


SemanticIndexing


Semantic indexing• We are drowning in an information tsunami

– Everyone faces the same problem: How to find the information

• Many people believe search engines are the solution...– ...but they only provide partial alleviation

• Topic Maps provides a better solution– Subject-based organization (everything organized around topics)– Associative model (very intuitive navigation)– Structured queries (adds more power to full-text search)

• Semantic indexing applications– Taxonomy management– Metadata management– Semantic portals


Taxonomy Management• Addresses the problem of managing unstructured content

– Solution is to organized by subject –that’s how users search– Many companies understand need to use taxonomies

• A taxonomy is a simple form of topic map– Topic Maps provides subject-based organization de-luxe

• Using Topic Maps offers many benefits:– Associative model allows for evolution beyond simple hierarchies– Taxonomy can also be used as a thesaurus, a glossary or an index

• This capability can also be added to ContentManagement Systems– (see other presentations later today)

http://www.idealliance.org/papers/dx_xmle04/papers/04-01-03/04-01-03.html


• Norwegian Government Administration Services metadata server– Manages metadata for official

publications using Topic Maps– Ensures consistency– Used in the central public

information portal (ODIN)

• The system provides– Authoring system for editors– Vocabulary Editor– Metadata Export– Web Services– Unique identifiers for

documents

Metadata Management

ODIN

Lovdata

Exported subjects ASCII-export

Metadataserver

MUP

Indexes

Engi

neODINMeta-data …

Search engine

Logistics


Semantic portals

• Basic principals– Site structure is defined as a topic map– The topic map ontology IS the Information Architecture– Each page represents a topic (i.e., subject-centric)– User-friendly navigation paths defined by associations– Topics used to classify content (replaces hierarchical

classification)

• Portals can be connected using remote access protocols to exchange topic map fragments– Can evolve over time into a Knowledge Management solution


Portals Powered by Topic Maps• Information

Architecture for web applications

• Used for web sites, portals, corporate intranets, etc.

ClientClient

Portlet

Portlet

Portlet

Portlet

Context Topic Map

Portlet

Subsystem Subsystem Subsystem

Portlet


Many Such Portals in Norway• One example:

The Works of Henrik Ibsen

• Famous Norwegian dramatist– Wrote Peer Gynt, Hedda Gabler,

A Doll’s House, etc.– A national icon for Norway– Died 1906: This year is 100 year

anniversary

• 8-year project to digitize everything he wrote (plays, letters, articles, etc.)

• Semantic indexing for the online version is based on Topic Maps


For General Users and Specialists

XML

Navigasjon ogaggregert informasjonAssosiativ navigasjon,tidslinje, indeks over verk,personer, steder, m.v.

Tekstmateriale – verk,varianter og kommentarerHovedtekster, noter ogkommentarer, varianterog variantsammenligningXML-databasen

Emnekart

KunnskapslagAllmen interesse,verdifullt for alle brukere

Vitenskapelig orientertHøy verdi for forskereDelvis utilgjengelig for andre

XML

Navigasjon ogaggregert informasjonAssosiativ navigasjon,tidslinje, indeks over verk,personer, steder, m.v.

Tekstmateriale – verk,varianter og kommentarerHovedtekster, noter ogkommentarer, varianterog variantsammenligningXML-databasen

Emnekart

KunnskapslagAllmen interesse,verdifullt for alle brukere

Vitenskapelig orientertHøy verdi for forskereDelvis utilgjengelig for andre

Knowledge layerGeneral interestValuable for all users

Scientific orientationHigh value for researchersPartly closed for others

Navigation and aggregated informationAssociative navigation, timeline, index of works, people, places, etc.

Text material – works, variants, commentariesMain texts, letters, notes, commentaries, variants and comparative material

Topic Map

XML database


sent year published year

mentions

sent to

mentions

sent from

Placedescription

Rome

Letter

Letter toBjørnson

Persondescription

BjørnstjerneBjørnson

Persondescription

ClemensPetersen

Work

Peer Gynt

Rome

Letter toBjørnson


ClemensPetersen

Peer Gynt

Year 1867


sent year published year

mentions

sent to

mentions

sent from

Rome

Letter toBjørnson


ClemensPetersen

Peer Gynt

Year 1867

Catilina (1850)Catilina er utgitt i to ganger, først i 1850, og senere i en bearbeidet versjon i 1875. Forskjellene mellom de to tekstene er betydelige, og de regnes derfor som to separate verk.

Ibsens brev om CatilinaCatilina omtales i flere av Ibsens brev:

• Brev til Ole Carelius Schulerud (15.10.1849)• Brev til Ole Carelius Schulerud (05.01.1850)• Brev til Kong Karl 15. (10.03.1863)• Brev til Peter Hansen (28.10.1870)

Les Catilina (1850)Dette er en forsiktig omarbeidet versjon av grunnteksten med rettelser og noter fra prosjektets tekstforskere.

• Første akt• Annen akt• Tredje akt• Fjerde akt

Ibsen skrev også en senere versjon av Catilina: Gå til Catilina (1875)

TekstarkivFølg tekstutviklingen til Catilina:

• 5 manuskripter • 6 utgaver • Faksimiler• Sammenligning av tekstkilder

Gå til tekstarkivet

Kommentarer og innledning Bakgrunn og informasjon om Catilinafra prosjektets tekstforskere:

• Bakgrunn• Tilblivelse• Utgivelse• Oppførelse• Tekstkritisk redegjørelse• Manuskriptbeskrivelse• Litteraturliste• Tillegg

Fra uroppførelsen av Catilina ved slik og slik teater, sted i 1851.

Bildearkivet inneholder 32 bildertilknyttet Catilina (1850):Gå til bildearkivet

Hva skjedde i 1850Geografi• Kristiania

Dikt• I natten• Guldharpen• Bjergmanden(totalt 12 dikt)

Brev• Til kong Oscar 1. (12.07.1850) • Til Clara Ebbell (nyttår 1850/51)• Til Cathrine Martini (12.04.1850)(totalt 23 brev)

Se alt som skjedde i 1850

http://images.google.no/imgres?imgurl=http://home.no.net/espenore/GriegIbsen/bilder/pg2.jpg&imgrefurl=http://home.no.net/espenore/GriegIbsen/tekster/Uroppfoerelse.html&h=480&w=747&sz=50&tbnid=q4DpxHdoeHJOXM:&tbnh=89&tbnw=140&hl=no&start=4&prev=/images%3Fq%3Dpeer%2Bgynt%26svnum%3D10%26hl%3Dno%26lr%3D%26sa%3DN

Bjørnson, Bjørnstjerne Martinius1832-1910, norsk forfatter

Prestesønn. Født i Kvikne (nå Tynset), Hedmark og flyttet 1837 til Nesset sogn i Romsdal, der familien bodde til 1853, da faren overtok Søgne prestekall. Etter skoleår i Molde reiste han 1850 til Kristiania. Elev på "Heltberg Studentfabrikk," der han møtte Ibsen, Lie og Vinje. 1852 examen artium med karakteren non. Vinteren 1852-53 huslærer for sine søsken hjemme på Nesset. Høsten 1853 leste han til anneneksamen, men avbrøt studiet og bestemte seg for å bli dikter. Prestesønn.

Les mer om Bjørnstjerne Bjørnson ...Ibsens omtaler av BjørnsonBjørnson omtales i flere tekster:

• Brev til bernhard dunker 22. juni 1864 • Brev til bernhard dunker 7. mars 1864 • Brev til christian tønsberg 11. november 1866 • Brev til clemens petersen 10. august 1863 • Brev til den gyldendalske boghandel 5. mars 1871 • Brev til det kongelige norske videnskabers selskab 25. mars 1865 • Brev til edvard grieg 24. august 1866 • Brev til frederik hegel 11. april 1870 • Brev til frederik hegel 12. februar 1870• Brev til clemens petersen 10. august 1863 • Brev til den gyldendalske boghandel 5. mars 1871

Brev fra Ibsen Mottok følgende brev fra Ibsen:

• Brev til Bjørnstjerne Bjørnson (15.10.1854)• Brev til Bjørnstjerne Bjørnson (15.10.1855)• Brev til Bjørnstjerne Bjørnson (15.10.1856)• Brev til Bjørnstjerne Bjørnson (15.10.1857)• Brev til Bjørnstjerne Bjørnson (15.10.1858)

Brevenes innholdIbsen tar opp en rekke ulike emner i sine brev til Bjørnson:

Personer• Bjørnson, Karoline (8)• Dunker, Bernhard (5)• Ibsen, Susanna (4)Vise alle ...

Steder• Christiania Theater (7)• Norge (5)• Stortinget (4)Vise alle ...


Pansori Web Site

• Created by INEK– Korean folk music

• Subject of a usability study

0

50

100

150

200

250

300

T1 T2 T3 T4 T5 T6 UserQuery

M ean

CPRS

TMPRS

www.inek.co.kr


EnterpriseInformationIntegration


Information integration• Information is often

spread across multiple systems

• Use Topic Maps to provide a single point of access to all information

• You can avoid costly migration and re-engineering


EII: Why Topic Maps are Ideal• Very flexible data model

– Hierarchical (XML), relational (RDBMS), associative (RDF) data can be easily mapped to topic maps

• Topic maps can be merged– You can generate topic maps from structured data– You can classify unstructured content topic map taxonomy– And then you can merge the topic maps to provide a unified view

• Topic maps can be filtered– You can create personalized views of the unified information

• Advantages:– Consolidated access to all related information– Does not require migration of existing content– Standards-based

http://www.ontopia.net/© 2006 Ontopia AS Source repository

TElmer

Bug database

C++ class TBug

TRequirement

caused bybreaks

Requirements DB

Example: Starbase Elmer• Project is to build a server for integrating software information

• Multiple applications hold related data– Unified topic map layer on top allows searching across repositories– Provides data integration without changing the underlying applications

• Access to information provided through a portal– Straightforward navigation interface– Structured queries

• Topic map drivesintegration with MSOffice Smarttags

– Elmer terms are highlighted– Appear as links back into the

portal


KnowledgeManagement


Knowledge Management / eLearning• Every organization faces the challenge of managing knowledge

– Capturing and sharing knowledge in people’s heads

• Why are Topic Maps ideal for this?– Because the model captures knowledge– Because topic maps can be merged– And because it is an ISO standard

• Some examples (there are many more)– Business process management– Product configuration– Business rules management– IT asset management– Manufacturing asset management– Intelligence gathering and analysis


Business Process Modelling• Managing business process models

– The flexibility of the Topic Maps model allows arbitrary relationships to be captured easily

• Processes are modelled in terms of– The steps involved, their preconditions, their successors, etc

• Can be related through– Composition (one process is

part of another),– Sequencing (one process is

followed by another),– Specialization (one process is

a special case of a moregeneral process)


Product Configuration• Using topic maps to manage complex product configuration

for mobile phones– Products belong to families– Features belong to products or product families– Features are grouped in feature sets– Dependencies between features; different geographic applicability

• Network of dependencies is already quite complex– Versioning makes it much worse– Managing all this data is not easy

• Dependencies modelled in a topic map– Product configuration engineers use this to

configure products using a very user-friendly interface

• Allows integration with product documentation

FeaturesProductfamilies

Products

System data

Versioning


Business Rules Management• Managing guidance rules for security classification

– Information about the production of nuclear weapons– Subject to 1,000s of rules published in 100s of documents– Most documents are derived from more general documents

• This complex web of relationships is capturedin a topic map– Concepts are connected to if-then-else rules– This constitutes a knowledge base

• Inference engine automatically– classifies information– redacts information

Guidancetopic

Parenttopic

Childtopic

Mastertopic

Derivedtopic

Concept

Responsibleperson

Workflowstate


IT Asset Management• Management of IT assets at University of Oslo

– Servers, clusters, databases, etc described in a TM

• This is used to answer questions like– Service X is down, who do I call?– If I take Y down, what else goes?– If operating system Z is upgraded,

what apps are affected?

• System driven by compositetopic map– Partly autogenerated– Partly handcoded

XTM RDBMS backend

usit.ltm(handcoded)

oracle.ltm(generated)

• Syntax control• OKS schema

validation• Versioning with

CVS

CVS

Topic Map Engine

Navigator frameworkOKS API

UIOTM FW

Houdini Whitney


Asset Management: Manufacturing• US Department of Energy uses

Topic Maps to “map” its production facilities for nuclear weapons

• The purpose is to get an overview of– equipment,– processes,– materials required,– parts already built,– etc.

• Cannot show you a screen shot– Otherwise I will be shot

http://www.mulberrytech.com/Extreme/Proceedings/html/2004/Mason01/EML2004Mason01.html


Intelligence Agencies – Lots of Data

• Everything isinterconnected...

• The problem for intelligence agencies is to find, record and utilize the connections

Islamic Salvation

Foundation

July 22, 2004 in

Baghdad, Iraq

IraqRole: Country

Base of

Operations for

Al QaedaRole: Terrorist

Organization

Location of

Method of Attack Beheading


Merging Knowledge Models

USS CHEYENNE (SSN 773)

Currently anchored

in

Role: Vessel

Knowledge maintained by ONI

Has active

agents of

LebanonRole: Country

HamasRole: Terrorist

Group

Knowledge Maintained by another intelligence organization

BeirutRole: City

LocatedIn

BeirutRole: City


Merging Knowledge Models• Knowledge models are merged

from separate applications, between departments, or between organizations.

• Knowledge is maintained by the experts closest to it, but merged freely to create models beyond the expertise of a single group.

• Knowledge-driven applications are enhanced as new models are merged into the solution.


Tying All the Data Together

Knowledge Layer

<data>

<country>

</country>

. . .

</data>

Weapons database

VesselSpecification Documents HTML

Documents

portal

pda

custom app

web

SoftwareCode


eLearningApplications


eLearning applications

• Knowledge is at the core of eLearning– The acquisition of knowledge by humans

• Topic Maps provides anexcellent model

• It can be used to– Capture what the pupil has learned– Structure eLearning systems– Organize school and university curricula– Tie all of this together


Competency goals

GradeTopic Individualgoals


Subject (with code)

Integration with Course Management Systemsvia the subject (here: “Naturfag” = “Science”)


Integration with portals offering career adviceor information about further education courses


Vilbli.no

Udir.no

Skolenettet.noYou name it...

Pupilslearning platform

Local curricula

Integrating the Education System


E-learning• Topic maps are associative

knowledge structures– They reflect how people

acquire and retain knowledge

• BrainBank is used by students to describe what they have learned– Initial users are 11-13 year

olds who have no idea what a topic map is…

– They capture the key concepts, name them, describe them, and associate them with others


Some Benefits of BrainBank• Enables pupils to

– Capture the essence of their new knowledge,

– Describe what they have learned,– Keep track of their knowledge, and– Lets the teacher help them

• Encourages a new way of learning– Pupils construct knowledge by

“fitting” it together with existing knowledge

– This is like adding a topic to a topic map and associating it with pre-existing topics


A National Knowledge Base

• Our experience from Norway– As more Government Agencies adopt Topic Maps, a

distributed National Knowledge Base starts to emerge

• Topic Maps can be merged on-the-fly so that knowledge is connected across agencies

• Published Subjects can be the infrastructure on which a National Knowledge Base is built– A Semantic Superhighway of unique topic identifiers– Foundation for Topic Maps and Semantic Web


The National Knowledge Base

SNL

SNL

SNL

SNL

Skienkom-mune

CapLex

CapLex

NBL

Henrik Ibsen

Hedda Gabler

Skien

Et dukkehjemA doll’s house

wrote

born in

wrote

“real world”

topic map

information

knowledge

Other Topic Maps can be merged in

Ibsen-senter

Ibsen-senter

Ibsen-senter

Ibsen-senter

Ibsen-senter

Ibsen-senter

Et dukkehjemHelmerHelmer

Dr. RankDr. RankMrs. LindeMrs. Linde

KrogstadKrogstadNoraNora


Conclusion

• Topic Maps can be used for many different purposes in industry, public sector, and academia– The principal applications are in semantic indexing,

information integration, knowledge management, and e-learning

– The benefits can be very great

• With a carefully planned strategy, Topic Maps can lead to the emergence of a National Knowledge Base in the Three Kingdoms


Topic Maps and the Semantic Web

• Some people think RDF/OWL and Topic Maps are competitors– (RDF/OWL are languages of the Semantic Web)

• Semantic Web gets much more publicity– Partly because the W3C can bask in the glamour of the Web– Partly because RDF and OWL appeal more to academics

• Why the perceived competition with Topic Maps?– Partly because RDF/OWL and TMs have a number of similarities– Partly because they stem from rival organizations (W3C and ISO)– Partly because there are a few bigots (in each camp)– Mostly because people do not fully understand the difference


Similar in Many Ways• Both “extend” XML into the realm of semantics

• Both allow assertions to be made about subjects in the outside world

• Both define abstract, associative (graph-based) models

• Both are intensely concerned with “identity”

• Both allow some measure of inferencing or reasoning

• Both have XML-based interchange syntaxes

• Both have constraint languages and query languages

• ...

• But they are also different in some crucial respects…


The Most Crucial Differences

• RDF/OWL is for machines;Topic Maps is for humans.

• RDF/OWL is optimized for inferencing;Topic Maps is optimized for findability.

• RDF/OWL is based on formal logic;Topic Maps is not based on formal logic.

• RDF/OWL is to mathematics asTopic Maps is to language.


RDF or Topic Maps: Some Rules of Thumb• Do you simply want to encode document metadata?

– RDF is ideal and you won’t need OWL

• Do you want to achieve subject-based classification of content?– Topic Maps combines flexibility and user-friendliness

• Do you want both metadata and subject-based classification?– Go straight for Topic Maps, because it also supports metadata

• Do you want to develop agent-based applications?– Use RDF/OWL; if you already have Topic Maps, it’s a good start

• Whatever you choose, know that you can move your data between Topic Maps and RDF, thanks to the RDFTM work…


The RDF/TM Task Force• A W3C task force supported by the ISO Topic Maps group

– Chartered to address RDF/Topic Maps interoperability– Working within the Semantic Web Activity of the W3C

• Survey of RDF/Topic Maps Interoperability Proposals– http://www.w3.org/TR/rdftm-survey/

• Guidelines for RDF/Topic Maps Interoperability– http://www.ontopia.net/work/guidelines.html (draft)

• Focus on data interoperability:– “The primary goal of these Guidelines is to enable data to be

translated from one form to the other without unacceptable loss of information or corruption of the semantics. Further goals are to be able to query the results of a translation in terms of the target model and to share vocabularies across the two paradigms.”