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Toma

Toma - TMQL, TMCL, TMML

Book Chapter, was published by Rani Pinchuk, Richard Aked, Juan-Jose de Orus, David De Weerdt, Georges Focant, Bernard Fontaine, and Els Dessin at 2007-09-04

This chapter presents Toma, a Topic Map Query Language.

External Link: download paper

Toma is a Topic Map Query Language, Topic Map Manipulation Language and Topic Map Constraint Language. Although its syntax is similar to that of SQL, it has a powerful path expression syntax which allows to access elements of the topic map. Toma offers the SELECT, INSERT, UPDATE and DELETE statements, used to query and manipulate the topic map. The MERGE statement is used to merge topic maps, and the EXPORT statement is used to export the topic map to XTM. Set of statements are provided for defining and managing constraints. Finally, Toma provides functions which allow to modify, convert and aggregate the data coming from the topic map.

Authors

Rani Pinchuk

No contact information available. 

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Rani is involved in LINDO, DIADEM, ULISSE, TopiEngi, and SATOPI.

Richard Aked

No contact information available. 

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Richard is author of TopiMaker – An.. , TopiWriter - Integrating.. , and Toma - TMQL, TMCL, TMML.

David De Weerdt

No contact information available. 

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David is author of TopiMaker – An.. , TopiWriter - Integrating.. , and Toma - TMQL, TMCL, TMML.

Georges Focant

No contact information available. 

Signet_person

Georges is author of TopiWriter - Integrating.. and Toma - TMQL, TMCL, TMML.

Presented at

TMRA 2006

Conference in Leipzig from {{start}} to {{end}}

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TMRA – the international conference series on Topic Maps Research and Applications – is a scientific and industrial forum whose main object is …

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As a former information scientist, I am fascinated since 1999 by the capabilities for building Topic Maps-based knowledge systems having the potential to augment human mind. One can model arbitrary knowledge organization systems, deal with semantic heterogeneity, collocate all facts about one subject in one logical place, and with TMQL have semantic retrieval on federated semantic networks. Therefore I expect bright prospects for business concepts building on the exchange of such knowledge snippets via semantic knowledge services.

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Alexander Sigel
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Topic Maps Lab auf der Cebit 2011
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