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Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
Hendrik Thomas - Semantic Web - Topic Maps 2009
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Hendrik Thomas - Semantic Web - Topic Maps 2009

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A detailed introduction to the ontology modelling language Topic Maps including a hands-on tutorial

A detailed introduction to the ontology modelling language Topic Maps including a hands-on tutorial

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  • 1. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Introduction to Topic Maps 23/02/2009 Dipl.-Wirt.-Inf. Hendrik Thomas University of Dublin Trinity College Trinity College, Knowledge Management HT 2009 1
  • 2. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Outline 1. Part: Lecture (Today) ● Information retrieval challenges ● Introduction to Topic Maps ● Process model for the design Topic Maps ● Important modeling questions & guide lines 2. Part: Lab Exercise (Wednesday) ● Topic Maps Editor ● Modeling of a sample Topic Map Trinity College, Knowledge Management HT 2009 2
  • 3. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Information Retrieval Challenges fundamental problems: ● information flood gigantic amount of information (invisible web)  heterogeneity of data (txt, movie, pic) ● information deficiency ● information losses reading cages of the Marsh’s Library, 1701 objective: efficient, comprehensive and simple access to knowledge Trinity College, Knowledge Management HT 2009 3
  • 4. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Introduction to Topic Maps ● Topic Maps is a ISO-standard for encoding knowledge & the connection with relevant information resources (ISO/IEC 13250: Topic Maps)  http://www.isotopicmaps.org/sam/sam-model/ ● objective of Topic Maps formal modelling of relevant knowledge aspects and its structure = semantic information ● domains of applications: ● organisation of information spaces (e.g. digital libraries) ● management of information and knowledge ● interoperability and exchange of knowledge Trinity College, Knowledge Management HT 2009 4
  • 5. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Origins of Topic Maps: book indexes Associations Gorda Sound see North Sound Little Dix Bay .................... 89 North Sound ....................... 90 Road Harbour see also Road Town ... 73 Road Town ...................... 69,71 Spanish Town ................... 81,82 Tortola ........................... 67 Virgin Gorda ...................... 77 Topics Occurrences Trinity College, Knowledge Management HT 2009 5
  • 6. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Basic elements of a Topic Map (TAO) ● Topics (nodes) represent all relevant subjects Trinity ● Associations (edges) College represent relations between the subjects Hendrik Thomas ● Occurrences connect subjects with relevant information resources CV Steve Pepper: The TAO of Topic Maps - Finding the Way in the Age of Infoglut, 2002 http://www.ontopia.net/topicmaps/materials/tao.html Trinity College, Knowledge Management HT 2009 6
  • 7. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Topics ● topics are surrogates or “proxies” (inside the computer) for the subjects that you want to talk about ● subject can be anything = persons, objects, thoughts (abstract or real) ● each subject is represented by exactly one topic! ● objective: topics become “binding points” for everything that is known about a given subject topic as a digital representation subject in the real world Trinity College, Knowledge Management HT 2009 7
  • 8. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Topic Names ● topics can have multiple names ● application can choose appropriate names depending on context ● more than one language ● synonyms ● examples: TU Ilmenau (patent documents) ● University of Applied Science in Ilmenau ● Technische Hochschule Ilmenau ● TU-Ilmenau ● TUI ● Technical University of Ilmenau Trinity College, Knowledge Management HT 2009 8
  • 9. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Topic Types ● topic types represent a group of similar topics ● a topic type represents the class of which the topic is an instance ● examples: ● Topic „Angela Merkel“ is of the topic type „human“ ● Topic „Trinity College” is of the topic type „university“ ● topic types are topics  every topic can be modeled Trinity College, Knowledge Management HT 2009 9
  • 10. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas XTM Version 1.0 – Topic Maps XML Representation Unique identifier in the topic map <topic id=“123”> Can be system assigned <baseName> <baseNameString>Spanish Town</baseNameString> </baseName> <instanceOf> Topic Name <topicRef xlink:href=“#Town”/> </instanceOf> Topic Type </topic> <topic id=“Town”> <baseName><baseNameString>Town</baseNameString> </baseName> </topic> XTM Version 1.0 Standard http://www.topicmaps.org/xtm/ Trinity College, Knowledge Management HT 2009 10
  • 11. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Occurrences ● occurrence model relations between information resources and topics ● occurrences can be everything (files, database tables, etc.) ● occurrences can be ● external: reference to an external resources = URL ● internal: key-value-pairs as part of the topic map ● occurrence types are topics Trinity College, Knowledge Management HT 2009 11
  • 12. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas XTM Version 1.0 – Topic Maps XML Representation <topic id=“789”> <baseName> <baseNameString>Dublin</baseNameString> </baseName> Occurrence Type <occurrence> External Occurrence <instanceOf> <topicRef xlink:href=“#portal”/> </instanceOf> <resourceRef xlink:href=“http://dublin.ie” /> </occurrence> <occurrence> <instanceOf> <topicRef xlink:href=“#size”/> </instanceOf> Internal Occurrence <resourceData>117,8 square km</resourceData> </occurrence> /topic> Trinity College, Knowledge Management HT 2009 12
  • 13. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Subject Identification • subject locator (URL)  if a topic represents a Dublin -http://de.wikipedia.org /wiki/Ilmenau - addressable object »Topic« »Subject Locator« »Subjekt« e.g. webpage, picture • subject identifier (URL) »Subjekt Indicator« Dublin  if a topic represents a The capital of the irisch nation non-addressable object, is Dublin, situated at the east cost of the u-- e.g. a town, me, you »Subject Identifier« i ki/ Il me na irland … PSI rg /w ia.o i ped  Published Subject Indicator (PSI) t p:/ / de. w ik - -ht create a common vocabulary Dublin Dublin »Topic« »Subjekt« Trinity College, Knowledge Management HT 2009 13
  • 14. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas XRM 1.0 - XML Representation <topic id=“Dublin”> Subject identifier <subjectIdentity> <subjectIndicatorRef xlink:href="http://www.wikipedia.ie/dublin"/> </subjectIdentity> </subjectIdentity> PSI </topic> <topic id=“DublinMap”> Subject locator <subjectIdentity> <resourceRef xlink:href="http://www.wikipedia.ie/dublin/map.jpg"/> </ resourceRef > </subjectIdentity> </topic> Trinity College, Knowledge Management HT 2009 14
  • 15. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Merging – automatic integration of Topic Maps Topic Map A Topic Map B »Subject-Identifier« »Subject-Identifier« http://wiki.de/ilmenau http://wiki.de/ilmenau two topics will be merged, Ilmenau »Topic« Ilmenau »Topic« if both have an equal: »Occurrence Type« »Occurrence Type« Zip Code Postleitzahl Inhabitants • subject identifier (PSI) 98693 26540 • subject locator »Internal Occurrence« »Internal Occurrence« Topic Map C MERGING • item identifier (topic id) • … »Occurrence Type« Zip Code »Internal Occurrence« 98693 »Subject-Identifier« »Internal Occurrence« Ilmenau http://wiki.de/ilmenau 26540 Inhabitants Trinity College, Knowledge Management HT 2009 »Occurrence Type« 15
  • 16. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Associations (1/4) ● associations represent relations between topics (subjects) e.g. „Dublin“ is part of „Ireland“ ● topics and associations constitute the semantic network ● associations have always one type („is_a“, „part_of”, etc.) ● association types are topics  every association type can be modeled Trinity College, Knowledge Management HT 2009 16
  • 17. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Association Roles (2/4) pupil of Alexander Philosopher ● associations are not directed the great Aristotle ● associations have roles (similar to UML) education-relation Alexander the great Philosopher Aristotle Role: pupil Role: teacher Trinity College, Knowledge Management HT 2009 17
  • 18. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Associations (3/4) Alexander der Große Aristotle Trinity College, Knowledge Management HT 2009 18
  • 19. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Associations (4/4) association type: parent relation role: son role: mother role: dad Tom Mary Paul Trinity College, Knowledge Management HT 2009 19
  • 20. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas XTM 1.0 – XML Representation <association id=“12345678”> Internal ID <instanceOf> <topicRef xlink:href=“#teacher-pupil-relation”/> </instanceOf> Association Type <member> <roleSpec> <topicRef xlink:href=“#teacher”/> </roleSpec> <topicRef xlink:href=“#Aristoteles”/> Role Type </member> Role Player <member> <roleSpec> <topicRef xlink:href=“#pupil”/> </roleSpec> <topicRef xlink:href=“#AlexanderTheGreat”/> </member> </association> Trinity College, Knowledge Management HT 2009 20
  • 21. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Scopes • characteristics of topics: topic names, occurrences and roles • every characteristic is only valid in a specific context (scope) ● the name “Norge” for the topic Norway only in the language Norwegian ● an occurrence in the scope “user manual” ● an association “TM rule World” in the scope “fiction” • scopes define valid context in Topic Maps • benefits: context depended views + filter Trinity College, Knowledge Management HT 2009 21
  • 22. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas XTM Version 1.0 – Topic Maps XML Representation Scope <topic id=“123”> <baseName> <scope> <topicRef xlink:href=“#english”/> </scope> Topic Name <baseNameString>Spanish Town</baseNameString> </baseName> </topic> <topic id=“english”> <baseName> <baseNameString>English Language</baseNameString> </baseName> </topic> Trinity College, Knowledge Management HT 2009 22
  • 23. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Topic Maps = meta-layer for structuring a domain Trinity College, Knowledge Management HT 2009 23
  • 24. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Meta-Ontologies in Topic Maps ● Meta-Ontologies are build of: Ontology Level ● association types pub is located in town is part of country ● role types ● occurrence types O’brians pub Dublin Ireland ● name types Instance Level NO STRICT SEPERATION – a topic can be a type and an instance at the same time Trinity College, Knowledge Management HT 2009 24
  • 25. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Process model for the development of a topic map Preparation Implementation Analysis Documentation Rough Draft Detailed Draft Trinity College, Knowledge Management HT 2009 25
  • 26. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Who is involved in the modelling process? Person Tasks project manager control and coordination Experts provide domain knowledge User potential user of the Topic Maps based application Editor maintenance and input of data in the topic map Developer implements the Topic Maps based application ontology expert analysis of the domain and design of the topic map  combines all provided information and resources Trinity College, Knowledge Management HT 2009 26
  • 27. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Model example ● task: develop an information portal for Dublin city ● a lot of tourism, historical and sports related attractions ● multiple information and information sources ● opening hours ● event plans ● descriptions  information are scattered and difficult to access objective: model a topic map for this information portal Trinity College, Knowledge Management HT 2009 27
  • 28. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Process model for the development of a topic map Preparation Implementation Analysis Documentation Rough Draft Detailed Draft Trinity College, Knowledge Management HT 2009 28
  • 29. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 1. Phase: Preparation ● first steps: ● Define project goals and context of the project ● Collect all relevant information sources ● Workshops and interview with involved persons ● key question: ● Which knowledge domain should be modelled? ● Who are the potential users? ● Narrow down the modelling domain  define guidelines Trinity College, Knowledge Management HT 2009 29
  • 30. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 1. Preparation: Narrow down the modeling domain ● focus: boarders of the modeling domain ● What should be modeled and what not? ● Example: geological structure of the city ● granularity: level of details of the modeling ● What details should be modeled – where to stop? ● Example: every house in Dublin or only relevant once depend on knowledge domain  as much as necessary but no more Trinity College, Knowledge Management HT 2009 30
  • 31. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 1. Preparation: Project frame Question Answer knowledge domain target group focus granularity relevant sources Trinity College, Knowledge Management HT 2009 31
  • 32. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Process model for the development of a topic map Preparation Implementation Analysis Documentation Rough Draft Detailed Draft Trinity College, Knowledge Management HT 2009 32
  • 33. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 1. Phase: Analysis ● objective: ● identify detailed requirements ● analysis of the available information resources ● 1. source: structured data & unstructured data ● “Do not trust the schema/documentation” ● Murphy’s law ● 2. source: experts, file owner and user ● huge domain specific knowledge ● experts have very limited view = trained incapacity ● user provide open and praxis oriented view on problems result of the analysis: collection of potential concepts Trinity College, Knowledge Management HT 2009 33
  • 34. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 2. Analysis: Card-Sorting-Method Sport Sight rugby field FIT eis hall city hall gym Garrett Paul Durcan Fitzgerald Wicklow Ronan Mountains Keating Trinity College DUBLIN Sean Lemass Thomas Christ- Parnell church Howth Kilkenny Famous London Persons Cork Cities Trinity College, Knowledge Management HT 2009 34
  • 35. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Exercise – Your turn … ● develop a short concept collection for the information portal for Dublin city, please consider: ● relevant concepts ● relations between these concepts ● relevant classes Trinity College, Knowledge Management HT 2009 35
  • 36. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Process model for the development of a topic map Preparation Implementation Analysis Documentation Rough Draft Detailed Draft Trinity College, Knowledge Management HT 2009 36
  • 37. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft: Types ● unspecific definition of types: ● is a collection of things which have something in common ● is a collection of individuals which share at least one common attribute ● a type groups topic-map-elements together into a category where its elements are designated as instances of the type file:///C:/work_ibm/Dissertation/veröffentlichungen/07_Buch/Edit/type_samples_geo_form.jpg Trinity College, Knowledge Management HT 2009 37
  • 38. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft – Topic Types Hints ● a type has instances  if a type has no instances it is not a type ● if you ask if “foo” is a type, then simply check, if things exists which are “foos’” ● samples: ● Geography is a category but not a type = no instances ● Country is a type because things exists which are countries = Ireland, France are countries Trinity College, Knowledge Management HT 2009 38
  • 39. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft – Topic Types Germany Dublin Countries Countries Towns Cities Sightseens Sights Spire Cork Germany Dublin Townhall Killkenny Museum France Cork Museum Townhall Ireland Killkenny Spire Ireland France Trinity College, Knowledge Management HT 2009 39
  • 40. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft – Topic Types ● one topic type is often not precise enough ● a topic can have multiple topic types Ontology Level Building Sight Irisch Dublin Townhall Dublin Instance Level Trinity College, Knowledge Management HT 2009 40
  • 41. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft – Topic Types vs. Role Types ● instances are inescapably bound to a type  from the beginning of its existence till the end ● samples: ● person is a type, because someone is a person or not ● man or woman are also (relative) good types ● town mayor is a bad type because a person acts as mayor only during his election time frame  the rest of the time he is a “normal” person  role type it is sometimes difficult to separate topic types and role types Trinity College, Knowledge Management HT 2009 41
  • 42. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft: Topic-Typen vs. Role Types Dublin Working Place »Role Type« »Topic Type« Mayor Job-Relation »Association Type« Mayor »Role Type« »Instance« Person Person Trinity College, Knowledge Management HT 2009 42
  • 43. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft: Topic Names ● every topic should have at least one name human readable name ● choice of appropriate / default labels for subject is difficult ! ! ! ! ! »Concept« „Dublin“ »Object« »Term / Symbol« Trinity College, Knowledge Management HT 2009 43
  • 44. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 3. Draft: Create the network ● model instances of topics and associations  topics + associations = semantic network Trinity College, Knowledge Management HT 2009 44
  • 45. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Exercise – Your turn … ● develop a draft for a Topic Maps meta-ontology assign appropriate Topic Maps element to the concepts ● topic types ● association types ● association roles ● occurrences types (external + internal) ● topic names ● find instances (topics, associations, occurrences) Trinity College, Knowledge Management HT 2009 45
  • 46. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Process model for the development of a topic map Preparation Implementation Analysis Documentation Rough Draft Detailed Draft Trinity College, Knowledge Management HT 2009 46
  • 47. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 4. Documentation ● documentation of the meta-ontology of the Topic Maps ● list of the types + description ● Published Subject Identifier (PSI) ● Topic Maps graph  supports understanding Trinity College, Knowledge Management HT 2009 47
  • 48. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 4. Documentation ● Graphical Topic Map Notation (GTM) ● no official standard or commonly agreed method but ● use: GTMalpha Version 1.0 - see flyer! Trinity College, Knowledge Management HT 2009 48
  • 49. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Process model for the development of a topic map Preparation Implementation Analysis Documentation Rough Draft Detailed Draft Trinity College, Knowledge Management HT 2009 49
  • 50. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 5. Implementation – Topic Maps Exchange Formats ● objective: ● represent Topic Maps elements in a ● computer processable and exchangeable format ● many different exchange formats  obstacle to the TM development ● LTM – Linear Topic Map Notation ● XTM – XML Topic Maps (Version 1.0 and 2.0)  common standard for the exchange of topic maps Trinity College, Knowledge Management HT 2009 50
  • 51. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 5. Implementation – Topic Maps Editors ● (unfortunately) only few usable and useful tools  major disadvantage of Topic Maps ● Topic Maps editors: ● TM4L – Topic Map 4 E-Learning (open source) http://compsci.wssu.edu/iis/nsdl/download.html ● tmedit – Topic-Maps-Editor (open source) http://tmedit.org/ ● Ontopia Knowledge Suit (commerical but powerful) http://www.ontopia.net/download/freedownload.html Trinity College, Knowledge Management HT 2009 51
  • 52. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas 5. Implementation – Ontopia Knowledge Suite (OKS) ● OKS is a collection of different JAVA applications ● Omnigator – text based navigator ● Ontopoly – Ontology editor ● Vizigator – graph visualiser Trinity College, Knowledge Management HT 2009 52
  • 53. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Exercise for the next lab (1/2) ● Develop a draft for a Topic Maps ontology for a choose domain ● Create a project frame (objective, domain, focus, granularity, target groups) ● Develop a concept collection ● Assign appropriate Topic Maps element to the concepts ● topic types ● association types ● association roles ● occurrences types (external + internal) ● topic names ● Find at least 1 instance for every type Trinity College, Knowledge Management HT 2009 53
  • 54. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Exercise for the next lab (2/2) ● Download the OKS and task describtion https://www.cs.tcd.ie/~thomash/ ● Install the OKS and start the file startup.bat in the folder C:xxxoks-samplersapache-tomcatbin ● Start a web browser and open the following site http://localhost:8080/ ● Tasks: ● Model your topic map draft ● Export your topic map (XTM 1.0 + Topic map without schema) ● Create a second Topic Maps and merge both Topic Maps Trinity College, Knowledge Management HT 2009 54
  • 55. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Summary (1/2) ● ontology design is an art, not a science ● there is no single correct answer ● practice makes perfect ● many of the decisions depend on external factors ● the use of the ontology ● the organization that is going to use it ● systems connected to the topic map application ● the tools used on the application ● when in doubt, go for beauty Trinity College, Knowledge Management HT 2009 55
  • 56. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Summary (2/2) ● advantages: ● Topic Maps born out of long tradition of indexing ● Simple concepts: Topics, Associations, Occurrences ● Human friendly modeling approach: “map” ● Designed with merge ability in mind ● Concise vocabulary: approx 21 elements ● disadvantages ● only few use-cases & no killer application ● not enough tools and APIs ● Very small but passionate community, good commercial backing Topic Maps will rule the world but not yet! Trinity College, Knowledge Management HT 2009 56
  • 57. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Literature ● Lars Marius. Garshol, G. Moore: ISO/IEC JTC1/SC34, Information Technology – Document Description and Processing Languages, http://www.isotopicmaps.org/sam/sam-model/, 2006. ● Steve Pepper: The TAO of Topic Maps: Finding the Way in the Age of Infoglut. http://www.ontopia.net/topicmaps/materials/tao.html, 2002. ● Steve Pepper, Graham Moore: XML Topic Maps (XTM) 1.0, http://topicmaps.org/xtm/index.html, 2002. ● Lutz Maicher, Alexander Sigel und Lars M. Garshol (Hrsg.): Leveraging the Seman-tics of Topics Maps: Second International Conference on Topic Maps Research and Applications, TMRA 2006, Leipzig, Germany, October 2006, Revised Selected Papers, Berlin - Heidelberg 2007. Trinity College, Knowledge Management HT 2009 57
  • 58. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas Links Topic Maps engines: ● TMAPI – Common Topic Map Application Programming Interface http://www.tmapi.org/ ● tinyTIM – in memory TMAPI implementation Topic Maps editors: ● tmedit – Topic-Maps-Editor (open source) http://tmedit.org/ ● Ontopia Knowledge Suit (commercial) http://www.ontopia.net/download/freedownload.html ● TM4L – Topic Map 4 E-Learning (open source) http://compsci.wssu.edu/iis/nsdl/download.html Trinity College, Knowledge Management HT 2009 58
  • 59. Lecture Introduction to Topic Maps Dipl.-Wirt.Inf. Hendrik Thomas End Thanks for your attention! Trinity College, Knowledge Management HT 2009 59

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