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18 Feb 18
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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. However, the developers quickly realized that with a little additional generalization, they could create a meta-model with potentially far wider application. The ISO standard is formally known as ISO/IEC 13250:2003.
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There are different ways of notating topic maps graphically, in addition to GTM, listed below. One recently developed example is Topic Maps Martian Notation. TMMN (its acronym) is a simple graphical notation used to explain the Topic Maps data model, and map out both ontologies and representative instance data.[4] It is designed for use on whiteboard or paper, as well as within any diagram-based software including everyday presentation tools such as PowerPoint and OpenOffice.org. TMMN uses only a very small number of symbols – "blob", "label", "line", "dotted line", and "arrow" – to represent the relationships and basic elements of the topic maps model: topics, names, associations (and roles), scope, and cccurrences (including subject identifiers and subject locators). The "Martian" refers to the archetypal "Martian Scientist",[citation needed] namely, the ability to communicate knowledge across linguistic and cultural barriers, known and unknown. It was developed as part of the musicDNA project.[5] Advanced Topic Maps Martian Notation is currently under development by the musicDNA community and includes shorthand notation for various types of whole-part relationships.
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The semantic expressive power of Topic Maps is, in many ways, equivalent to that of RDF, but the major differences are that Topic Maps (i) provide a higher level of semantic abstraction (providing a template of topics, associations and occurrences, while RDF only provides a template of two arguments linked by one relationship) and (hence) (ii) allow n-ary relationships (hypergraphs) between any number of nodes, while RDF is limited to triplets.
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02 Nov 12
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27 Jan 11
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the major differences are that Topic Maps (i) provide a higher level of semantic abstraction (providing a template of topics, associations and occurrences, while RDF only provides a template of two arguments linked by one relationship) and (hence) (ii) allow n-ary relationships (hypergraphs) between any number of nodes, while RDF is limited to triplets.
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The definitions of allowed types is known as the ontology of the topic map.
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19 Dec 10
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27 Feb 08
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11 Jul 07
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04 May 07
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15 Jul 06
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09 Jun 06
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