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Spatial Identification of Subjects

Article, was published by Sven Krosse at 2010-09-30

This paper is about the spatial identification of subjects with a topic map.

Modeling information resources by using the Topic Maps paradigm has the great benefit that each real world subject has to be represented as exactly one resource item of the data model. Therefore, Topic Maps stores have to guarantee that two information items representing the same subject, will be merged automatically. Because of that the model should never contains a subject twice. The main problem are the weak identities of current Topic Maps engines, which are often defined by humans and not by domain-specific algorithms or patterns. The special domain of spatial (geographical) knowledge provides such an algorithm based on a standardized geographical system, like the WGS-84. In this case, a Topic Maps engine can provide a powerful algorithm for unique identities of subjects and, moreover, geographical information can also be used for additional knowledge about the subject.



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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.

Alexander Sigel
Topic Maps Lab auf der Cebit 2011

Graduate from the Topic Maps Lab