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H-Maps: An Efficient Approach for Graphical Visualization and Navigation of Topic Maps and Data Representation in Computational Biology

Paper, veröffentlicht von Markus Leber, Thilo Klöpfer und Steffen Hüttner am 12.11.2009

The paper presents overviews the new tool H-Maps.

Externer Link: more information

Nowadays semantic networks become more important in industry and modern science. For this reason there is a need for an efficient tool allowing preparation and navigation through complex data spaces. We present the novel Topic Map tool H-Maps, which offers a web based navigator providing an enhanced utilization and graphical visualization of semantic networks. Present applications transform existing content to subject-centric Topic Map representations in a one-way fashion. Preserving the advantage of transferring diverse back ends into a unified topic map in existing applications the H-Maps approach goes one step further. The resulting topic map structure can be examined and extended with an iterative procedure. Especially in science this procedure is leading to a considerable improvement of flexibility and performance as can be shown within projects of computational biology.

Präsentiert auf

TMRA 2009

Konferenz in Leipzig vom {{start}} bis {{end}}

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Call for Contributions TMRA 2009 will be the fifth event in the annual series of international conferences on Topic Maps Research and …

Zur Homepage von TMRA 2009

Projekte

H-Maps

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Hmaps1_650

H-Maps ist die Software-Antwort der Hölle & Hüttner AG zur Darstellung Ihrer Daten- und Informationsstrukturen. Auf Basis des 1999 festegelegten ...

Zur Homepage von H-Maps

Glossar

TMDM

ist assoziert mit {{count}} Einträgen.

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TMDM is the abbreviation for Topic Maps Data Model. You will find a compact illustration of all relationships within the TMDM

GTM

ist assoziert mit {{count}} Einträgen.

Signet_glossary

The acronym GTM stands for Graphical Topic Maps notation. GTM is a graphical notation used to define ontologies (level 1) and represent Topic Maps instance data (level 0).

 

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.

Alexander_sigel_2
Alexander Sigel
practical-semantics.com
Topic Maps Lab auf der Cebit 2011
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Graduate from the Topic Maps Lab