Topic Map (TM) (Danish: "emnekort")

"Topic map"  is an ISO standard for describing knowledge structures and associating them with information resources. They were created to be an ontology framework for information retrieval. Topic Maps have a rich semantic model that is well designed to support information retrieval in general, but can also be used for an almost unlimited range of other applications.


The work on TM began in 1991 when the Davenport Group was founded by UNIX system vendors and others. An important motivation was a pressure to improve consistency in their printed documentation. A major problem was to provide back-of-the-book indexes for independently created, constantly changing technical manuals aggregated into system manual sets.


TM is based on "the subject-centric view" as opposed to "the resource-centric view": 

"The topic maps paradigm recognizes that everything and anything can be a subject of conversation, and that every subject of conversation can be a hub around which data resources can orbit. Unlike the resource-centric view in which metadata orbits data resources, in the subject-centric view, data orbits subjects. If the subject itself happens to be a data resource, the orbiting data can, of course, be called metadata. But one of the essential lessons of the topic maps paradigm is that all data is data about subjects, but only some subjects are themselves data; most subjects are not information resources. When the problem of global knowledge interchange is approached with this subject-centric attitude, the solution becomes much simpler and easier. Indeed, for many people, and particularly for the people who have used it the most, the topic maps paradigm passes the most convincing test of all: the solution, once finally found, is obvious." (Newcomb, 2003, p. 43).


Some basic concepts in TM:

  • Names are the terms used about a topic [concept].

  • Occurrences connect the topics to information resources that contain information about them (by URIs).

  • Associations represent relationships between subjects,


The relation between TM and other kinds of knowledge organization systems (KOS) is described here:


"A summary of the relationship between topic maps and traditional classification schemes might be that topic maps are not so much an extension of the traditional schemes as on a higher level. That is, thesauri extend taxonomies, by adding more built-in relationships and properties. Topic maps do not add to a fixed vocabulary, but provide a more flexible model with an open vocabulary.

    A consequence of this is that topic maps can actually represent taxonomies, thesauri, faceted classification, synonym rings, and authority files, simply by using the fixed vocabularies of these classifications as a topic map vocabulary." (Garshol, 2004).


"Compared to traditional classification schemes this is very different. First of all, we no longer have a hierarchy but a network of subjects. Secondly, the relationships between the subjects are clearly defined instead of being generic. From the point of view of searching, this is very powerful, since it allows us to do queries like "show me all technologies used with topic maps", or "show me every interchange format based on SGML", and so on." (Garshol, 2004).


"Because not all subjects are electronic artifacts, however, we cannot provide an address for the subject. Instead, we provide an electronic surrogate for the subject, which (being electronic) can have an address. This surrogate we call a topic. Every topic acts as a surrogate for some subject. We say that the topic “reifies” the subject — or makes the subject “real” for the system. The creation of a topic that reifies a subject enables the system to manipulate, process, and assign characteristics to the subject by manipulating, processing, and assigning characteristics to the topic that reifies it. When we need an address for the subject, we give the address of a topic which reifies it, and acts as its surrogate within the system." (ISO 13250-1).

By using topic maps to represent metadata and subject-based classification it is possible to reuse existing classifications and classification techniques, while at the same time describing the world more precisely where desired.

XTM is XML-based Topic Maps.



Criticism: The terminology of topic maps seems quite idiosyncratic. We shall here compare TM terminology with what is considered usual terminology:


Subjects: The topic map standard defines subject, the term used for the real world “thing” that the topic itself stands in for. In ordinary terminology we would say that what are called "subjects" are the referents of concepts. (Cf., Reference). IN LIS terminology subjects (that are identified by subject analysis) is given a different meaning than the one used in TM(cf., subject).


Topics: "A topic, in its most generic sense, can be any “thing” whatsoever – a person, an entity, a concept, really anything – regardless of whether it exists or has any other specific characteristics, about which anything whatsoever may be asserted by any means whatsoever." "Strictly speaking, the term “topic” refers to the element in the topic map document (the topic link) that represents the subject being referred to." (Pepper (2002).  As already mentioned under subjects, normal terminology would say that what in TM are called "topics" should rather be termed "concepts".  The words topic and topicality is given different meanings in LIS (cf., topic).


Topic names: In usual terminology this are the symbols (or the kind of symbols called words) used to designate a concept.


Topic types: The topic map terminology says: "This corresponds to the categorization inherent in the use of multiple indexes in a book (index of names, index of works, index of places, etc.)". In ordinary terminology this correspond to categories, fundamental kinds of concepts.


Occurrences. In TM terminology is a given document is seen as an occurrence of a topic. In indexing theory what "occurs" is information about a given concept. We may say that a book is about psychology, meaning that it contains information about the concept "psychology", that it is an information resource for that concept. (An index term may refer to a document (or to a passage in a document) in order to help users identifying information). 


Occurrence roles: Pepper (2002) writes: "Occurrences, as we have already seen, may be of any number of different types (we gave the examples of “monograph”, “article”, “illustration”, “mention” and “commentary” above). Such distinctions are supported in the standard by the concepts of occurrence role and occurrence role type." In ordinary LIS terminology are this termed document types (or elements/parts of documents).


Topic associations: Pepper writes: "A topic association is (formally) a link element that asserts a relationship between two or more topics. Examples might be as follows:

  • “Tosca was written by Puccini”
  • “Tosca takes place in Rome”
  • “Puccini was born in Lucca”
  • “Lucca is in Italy”
  • “Puccini was influenced by Verdi” " (Pepper, 2002).

In ordinary terminology what are called "topic associations" are kinds of semantic relations (or meaning relations between concepts). Pepper seems to recognize this when writing: "the semantics of a topic having a type (for example, of Tosca being an opera) could equally well be expressed through an association (of type “type-instance”) between the topic “opera” and the topic “Tosca”. The reason for having a special construct for this kind of association is the same as the reason for having special constructs for certain kinds of names (indeed, for having a special construct for names at all): The semantics are so general and universal that it is useful to standardize them in order to maximize interoperability between systems that support topic maps."


"Independent topic associations" versus "anchors within the information resources":

"It is also important to note that while both topic associations and normal cross references are hyperlinks, they are very different creatures: In a cross reference, the anchors (or end points) of the hyperlink occur within the information resources (although the link itself might be outside them); with topic associations, we are talking about links (between topics) that are completely independent of whatever information resources may or may not exist or be considered as occurrences of those topics." (Pepper, 2002).


This correspond to the distinction from indexing theory known as assigned versus derived indexing. In assigned indexing are terms from a controlled vocabulary assigned to a document representation, in derived indexing are terms within the document representations (information resources) used as entry points. 


Facet: Pepper (2002): "A facet is simply a property; its values are called facet values. Facets are typically used for supplying the kind of metadata that might otherwise have been provided by SGML or XML attributes, or by a document management system. This could include properties such as “language”, “security”, “applicability”, “user level”, “online/offline”, etc." (Pepper, 2002). This use of the term "facet" is in strong conflict with the way this term is understood in LIS (cf., Facet and facet analysis). The term property should be preferred.


Theme. Theme is defined as “a member of the set of topics used to specify a scope”. In other words, a theme is a topic that is used to limit the validity of a set of assignments. Thus, the name “tosca” might be assigned to three different topics in scopes defined by the themes “opera”, “opera”+“character”, and “baking” respectively, thereby removing any ambiguity and reducing the chance of errors, for example when merging topic maps." (Pepper, 2002). This definition is circular in that scope is defined by themes and themes are used to define scope. This definition of theme do not match the way it is ordinarily understood (see: theme).


Scope. Scope is circularly defined in terms of themes (see above). A better definition of scope comes from Wikipedia (2006): "In computer programming in general, a scope is an enclosing context. Scopes have contents which are associated with them. Various programming languages have various types of scopes. The type of scope determines what kind of entities it can contain and how it affects them. Depending on its type, a scope can: * contain declarations or definitions of identifiers;* "








Garshol, L. M. (2004) Metadata? Thesauri? Taxonomies? Topic maps! Making sense of it all. Journal of Information Science, 30 (4). 378-391. Available online at:


ISO 13250-1: Topic Maps: Overview and Basic Concepts. ISO International Standard, ISO/IEC 13250:2000.


ISO/IEC 13250:1999. Topic Maps. Information Technology. Document Description and Processing Languages.


ISO/IEC 13250:2002(E). Second edition. Topic Maps. Information Technology. Document Description and Processing Languages.


ISO/IEC 13250:2003(E). Second edition. Information technology―SGML applications―Topic maps.


Newcomb, S. R. (2003). A perspective on the quest for global knowledge interchange. IN: XML Topic Maps: Creating and Using Topic Maps for the Web. Ed. by Jack Park & Sam Hunting. Boston, MA: Addison Wesley Professional (pp. 31-50).


Ontopia (2005). The Omnigator user guide. Oslo, Norway. Ontopia. Available online at:


Park, J. & Hunting, S. (Eds.). (2003). XML Topic Maps: Creating and Using Topic Maps for the WebBoston, MA: Addison Wesley Professional.


Pepper, S (2002). The TAO of Topic Maps. Available online at:



Pepper, S & Moore, G (2000). XML topic maps (XTM) 1.0. Available online at:


Schweiger, R. , Hoelzer, S. , Rudolf, D. , Rieger, J. & Dudeck, J. (2003). Linking clinical data using XML topic maps. Artificial Intelligence in Medicine 28, 103-115.

Siegel, A. (2000). Towards knowledge organization with Topic Maps. IN: Conference Proceedings XML Europe 2000, 12-16 June 2000, Le Palais des Congrès de Paris, Paris, France. GCA, 2000. (Session: "Topic Maps: The technical side", 14 June, 2000). pp. 603-611. Available:


Siegel, A. (2002). Topic Maps in Knowledge Organization. IN: XML Topic Maps: Creating and Using Topic Maps for the Web. Ed. by Jack Park & Sam Hunting. Boston, MA: Addison Wesley Professional. Available in manuscript at:


Tramullas, J. & Garrido, P. (2005). Constructing Web subject gateways using Dublin Core, RDF and Topic Maps. Information Research, 11(2) paper248. Available at


Wikipedia, the free encyclopedia. (2006). Scope (programming).



Ontopia. The topic map browser. (2005). The Omnigator user guide. Oslo, Norway. Ontopia. Available online at:


Topic Maps Org. Home page:



See also: Topic and topicality (Core Concepts in LIS)




Birger Hjørland

Last edited: 12-10-2006