© 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

© 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 –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

© 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

© 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 book into content and index knowledge layer information layer (index) (content)

© 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 the back-of-book index belongs information layer

© 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 Madame Butterfly

© 2003 Ontopia AS 7 Linking the Layers Through Occurrences The two layers are linked together –Occurrences are information resources that are pertinent to a given knowledge topic –The links (or locators) are like page numbers in a back-of-book index Puccini Tosca Lucca composed by born in composed by Madame Butterfly knowledge layer information layer

© 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 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 question Puccini Tosca Lucca Madame Butterfly

© 2003 Ontopia AS 9 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. “ 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

© 2003 Ontopia AS 10 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 Omnigator A free topic map browser from

© 2003 Ontopia AS 11 The Omnigator A free topic map browser Online demo:  Download: 

© 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 –Or view it online at Built using Ontopia’s flagship product –The Ontopia Knowledge Suite (OKS) –A complete Java toolkit for building topic map applications –Academic licenses available from

© 2003 Ontopia AS 13 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 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 –Or view it online at

© 2003 Ontopia AS 14 How the Omnigator Works J2EE Web Server e.g. Tomcat Omnigator Ontopia Topic Map Engine topic map pages http server client

current topic (multiple) names (multiple) types multiple occurrences multiple associations

© 2003 Ontopia AS 16 Topic Map Query Language ISO/IEC 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

© 2003 Ontopia AS 17 Topic Map Constraint Language ISO/IEC 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” –“ 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

© 2003 Ontopia AS 18 Advanced Concepts in Topic Maps Subject Identity Published Subjects Scope Reification

© 2003 Ontopia AS 19 COMPUTER DOMAIN 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 Madame Butterfly

© 2003 Ontopia AS 20 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 –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

© 2003 Ontopia AS 21 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 a subject 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 Best known for his operas, of which Tosca is the most... subject indicator Puccini subject identifier topic © 2002 Ontopia AS

© 2003 Ontopia AS 22 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: Guidelines for publishing PSI sets –geolang: A PSI set for geographical and language subjects Based on existing standards (e.g. ISO 639, ISO 3166) –xmlvoc: A PSI set for an ontology of XML and related standards

© 2003 Ontopia AS 23 Topic Map Merging The concept of Subject Identity makes it possible to automatically merge topic maps –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 name occurrence association role name A second topic (in another topic map) “about” the same subject T Merge the two topics together... Merge the two topics together......and the resulting topic has the union of the original characteristics name occurrence association role name T

© 2003 Ontopia AS 24 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

© 2003 Ontopia AS 25 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

© 2003 Ontopia AS 26 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 topic Germany in the scope “French” –the name “composer of” (for the association type “composed by”) in the scope “composer” –a certain information occurrence in the scope “technician” –a given association is true in the scope (according to) “Authority X” name occurrence association role name occurrence association role name T T occurrence association role name T Filtering by scope

© 2003 Ontopia AS 27 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

© 2003 Ontopia AS 28 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

© 2003 Ontopia AS 29 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

© 2003 Ontopia AS 30 For More Information “Getting Started with Topic Maps” –In your handouts Ontopia web site – /me 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)