Topic map

A __topic map__ is a standard for the representation and interchange of knowledge, with an emphasis on the findability of information. Topic maps were originally developed in the late 1990s as a way to represent back-of-the-book index structures so that multiple indexes from different sources could be merged - wikipedia

# Worldscape

The Worldscape Conference format uses topic maps to create argument maps around the talks and workshops that take place at an event.

Notabilia showing the 100 longest Article for Deletion discussions, which resulted in deleting the article - notabilia.net

The technology we have developed allows diverse conversations taking place at different locations, in different contexts, and at different times to be linked together, and visualised as a Slowly evolving dialogue.

# Specification

This specification provides a model and grammar for representing the structure of information resources used to define topics, and the associations (relationships) between topics.

Illustration of how the three key concepts relate in the Topic Map standard. These are topic, association and occurrence. - wikimedia.org

Names, resources, and relationships are said to be characteristics of abstract subjects, which are called topics.

A topic map represents information using: * __topics__, representing any concept, from people, countries, and organizations to software modules, individual files, and events, * __associations__, representing hypergraph relationships between topics, and * __occurrences__, representing information resources relevant to a particular topic.

Topics have their characteristics within scopes: i.e. the limited contexts within which the names and resources are regarded as their name, resource, and relationship characteristics.

# Ontology and merging Topics, associations, and occurrences can all be typed, where the types must be defined by the one or more creators of the topic map(s). The definitions of allowed types is known as the Ontology of the topic map - wikipedia

Topic Maps explicitly support the concept of merging of identity between multiple topics or topic maps. Furthermore, because ontologies are topic maps themselves, they can also be merged thus allowing for the automated integration of information from diverse sources into a coherent new topic map.

Features such as subject identifiers (URI (Uniform Resource Identifier)s given to topics) and PSIs (''Published Subject Indicators'') are used to control merging between differing taxonomies. Scoping on names provides a way to organise the various names given to a particular topic by different sources.

# Examples

# Sections

# See also