"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
indexes for independently created,
constantly changing technical manuals aggregated into system manual
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,
Some basic concepts in TM:
Names are the
terms used about a topic [concept].
connect the topics to information resources that contain
information about them (by
represent relationships between subjects,
The relation between TM and
other kinds of
knowledge organization systems (KOS) is described here:
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,
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,
"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.
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.
Reference). IN LIS terminology subjects (that are identified by subject
analysis) is given a different meaning than the one used in TM(cf.,
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 names: In usual terminology this are the
symbols (or the kind of symbols called words) used to designate a concept.
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).
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”
takes place in Rome”
- “Puccini was
born in Lucca”
- “Lucca is
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.
"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
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."
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:
Scope. Scope is
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
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
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.
Addison Wesley Professional (pp. 31-50).
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 Web.
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).
topic map browser. (2005). The Omnigator user guide. Oslo, Norway.
Ontopia. Available online at:
Topic Maps Org. Home page:
topicality (Core Concepts in LIS)