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Documentation for aircraft maintenance based on topic maps

Paper, was published by Kay Kadner and David Roussel at 2007-09-04

This paper defines a description language for storing Aircraft Maintenance Manuals based on Topic Maps.

External Links: download paper and ACM record

Fast and easy processing of documentation for maintenance and overhaul is of high importance for many companies, especially in the aircraft domain. The documentation of a certain aircraft often comprises thousands of pages, which today mostly exist as paper-based documents. To use the benefits of electronic technical manuals, we define a description language for storing Aircraft Maintenance Manuals (AMM) based on Topic Maps, which is called XTM-P (XML Topic Map for Procedures). Besides syntactic information, this language is used to capture semantic information for supporting smart adaptation to multiple output devices and modalities. Several concepts of this language are described.

Authors

Kay Kadner

No contact information available. 

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Kay is author of Documentation for aircraft.. .

David Roussel

No contact information available. 

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David is author of Documentation for aircraft.. .

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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glossary

XTM

is associated with {{count}} items.

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XTM is the abbreviation for Topic Maps XML Syntax. There are currently two versions: XTM1 and XTM2.

 

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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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