MedicalcnIformatisGroup i Indexes, Topic maps & the semantic net Dr Jeremy Rogers MRCGP Clinical...

Medical cnI formati sGroupi

Indexes, Topic maps Indexes, Topic maps

& the semantic & the semantic netnetDr Jeremy Rogers MRCGPDr Jeremy Rogers MRCGP

Clinical Research FellowClinical Research Fellow

Medical Informatics GroupMedical Informatics Group

University of ManchesterUniversity of Manchester


OutlineOutline

What’s an Index ?What’s a Topic Map ?

UsesStrengths & Weaknesses


What’s in an index ?What’s in an index ?La Bohème, 10, 70, 197-198, 326 Cavalleria Rusticana, 71, 203-204 The Girl of the Golden West, see La fanciulla del West Leoncavallo, Ruggiero

I Pagliacci, 71-72, 122, 247-249, 326 Madama Butterfly, 70-71, 234-236, 326 Manon Lescaut, 294 Mascagni, Pietro

Cavalleria Rusticana, 71, 203-204 Puccini, Giacomo, 69-71

La Bohème, 10, 70, 197-198, 326 La fanciulla del West, 291

Madama Butterfly, 70-71, 234-236, 326 Manon Lescaut, 294 Tosca, 26, 70, 274-276, 326 Turandot, 70, 282-284, 326 Rustic Chivalry, see Cavalleria Rusticana singers, 39-52, See also individual names

baritone, 46 bass, 46-47 soprano, 41-42, 337 tenor, 44-45

soprano, 41-42, 337 tenors, 44-45 Tosca, 26, 70, 274-276, 326 Turandot, 70, 282-284, 326

different different typestypes of topic (the names of of topic (the names of operas are shown operas are shown in italicin italic))

different different typestypes of occurrence of occurrence (references to synopses are (references to synopses are in boldin bold))

synonyms for the same topicsynonyms for the same topic

links to associated topics (links to associated topics (see alsosee also))

associations between different topics associations between different topics (e.g. between a composer and his (e.g. between a composer and his works)works)

supertype and subtype informationsupertype and subtype information


What’s a topic map ?What’s a topic map ?

• Very similar to an index except…• Implicit information made explicit

– Not represented in typographical conventions

• Consistent use of topics within indexes– Consistent use between indexes ?


What is a topic map ?What is a topic map ?www.topicmaps.org

http://www.ontopia.net/topicmaps/materials/tao.html

• Means to convey knowledge about resources – Knowledge embodied in a superimposed

layer– A ‘map’ of the resources

• Captures – the subjects of which resources speak– the relationships between those subjects– implementation-independent


What is a Topic Map ?What is a Topic Map ?

The central concepts in topic maps are:

Occurrences e.,g. a physical book, a web page= the page numbers

Associations e.g. ‘is-author-of’= ‘see also’ links

Topics e.g. ‘Shakespeare’, ‘Hamlet’= the list of subjects in an index


History of Topic MapsHistory of Topic Maps• 1993 first description of topic maps• 2000 ISO/IEC standard 13250:2000

– Used HyTM

• 2001 minor update– To include XTM

• Main protagonists today – (a small but active community)– Ontopia (Oslo)– Techuila (Oxford)– InfoLoom (New York)– TopicMaps.Org


An example:An example:Subjects OccurencesType

Shakespeare 1

Hamlet 2

Jonson 3

London 4

Stratford 5

Volpone 6

Play 7

Town 8

Associations

Person 9

Topics

An Example in XTM:An Example in XTM:<topic id=“2">

Shakespeare 1

Hamlet 2

Play 7

writtenBy

author

work

<topic id=“2"> <instanceOf><topicRef xlink:href="#7"/></instanceOf>

<topic id=“2"> <instanceOf><topicRef xlink:href="#7"/></instanceOf><baseName>

<baseNameString>Hamlet, Prince of Denmark</baseNameString>

<baseNameString>The Scottish Play</baseNameString></baseName>



<baseNameString>The Scottish Play</baseNameString></baseName><occurrence>

<instanceOf><topicRef xlink:href=“#plain-text-format"/>

</instanceOf> <resourceRef xlink:href=“#mybook.hamlet.page101“/>

</occurrence></topic>

<association><instanceOf>

<topicRef xlink:href="#written-by"/></instanceOf>








<topicRef xlink:href="#written-by"/></instanceOf><member>

<roleSpec><topicRef xlink:href="#author"/></roleSpec>









<roleSpec><topicRef xlink:href="#author"/></roleSpec><topicRef xlink:href="#1"/>

</member>










</member> <member>

<roleSpec><topicRef xlink:href="#work"/></roleSpec>
















</member> <member>

<roleSpec><topicRef xlink:href="#work"/></roleSpec><topicRef xlink:href="#2"/>

</member> </association>


Demo: OntopediaDemo: Ontopedia


What are they for ?What are they for ?• Indexing large resources you can’t

write in directly– Original ‘back of book index’ motivation

• Organising web sites– Some elements on a web page generated

from topic map• E.g. www.ontopia.net/operamap/

• Expert systems• Way of storing information flows &

audit trails– Or any other network of info, really


How do I make one ?How do I make one ?• By hand

– Very labour intensive, but usually highest quality– Some tools e.g. Ontopia, TMTab for Protégé,

TMDesigner

• Semi-automagically– If the original data is already well structured– Some language processing tools can help

• Automatic Transformation– Re-write other sources of the same information

• Useful websites– www.ontopia.net– www.techquila.com


Strengths of Topic Maps…Strengths of Topic Maps…• Good for large or dynamic

information sources– E.g. ‘2001 Tax Products’

CDROM from US IRS– E.g. www.quid.fr

• Better querying than a static index– ‘Find all composers who have

written an opera that was not first performed in Italy but was based on a work originally written by Shakespeare’

• Making it possible/easier to merge knowledge resources– allegedly


……and limitationsand limitations• Not so good for very large

information sources– E.g. The entire world wide web

(= ‘The Semantic Web’)– The ontology problem

• Different topics used differently • at different times & by different authors

• No inferencing (yet)– E.g. IF Aria sung-in Act I

AND Act I part-of ToscaTHEN Aria sung-in Tosca

• Limitations in what can be said– E.g. Child must have exactly one mother– E.g. Mother of a baby kangaroo must

also be a kangaroo


Current DevelopmentsCurrent Developments

• Standardising the query language– ISO/IEC 18048 TMQL

• Standardising the constraint language– ISO/IEC 19756 TMCL (based on OWL

?)• “All persons must be born somewhere”• “A person may have died somewhere”

• Experiments with inferencing


Topic maps vs. semantic Topic maps vs. semantic netsnets

A Semantic Net is any data structure network with nodes representing objects, classes or concepts, and the arcs representing relations between them (e.g.

is-a, part-of etc)

•Therefore, all topic maps are a kind of semantic net

•But not all semantic nets are topic maps– Because richer semantic nets may include e.g. cardinality– Not all semantic nets need external references

•Other kinds of semantic nets:– Mind maps– Entity Relation Diagrams & UML (databases)– Description Logics (ontologies)


SummarySummary• Topic Maps formalise back of book

indexing– Especially useful for electronic age– Makes the index machine-readable

• Aspirations for more– Usual plans for global domination

• Relatively young– Details still being finalised– Low uptake so far– But key exemplars

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