This HTML5 document contains 26 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

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JANZZon! (system)
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The system of JANZZon! (the organization of concepts) follows logical criteria, but is also strongly content-driven, focusing on the content of the particular concepts. Background knowledge to the individual terms (their specific content) and the respective indexing of the concepts in the ontology are crucial, because a machine can only “learn” about terms and their significance by the availablilty of this knowledge. Occupations and functions can be organized relatively easily following logical criteria. Hierarchies are rather clear and the structuring of branches is not very complicated. Occupations can therefore be classified and indexed according to different industries and especially existing (international) occupation classifications. Somewhat more complicated to organize are the specializations and skills. A strict logical order is often difficult or not possible at all. For indexing and organizing in the ontology, a specific skill, specialization and the person holding this skill or specialization is the focus and starting point. Example Microsoft Word is clearly related to the concept Microsoft Office, a software. But, Microsoft Word is also often associated with Text processing, still it does not necessarily make sense to subordinate Microsoft Word Text processing. In order that the machine is still able to establish the connection between Microsoft Word and Text processing, both concepts can be linked to each other through relations.
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Embedded HTML5 Microdata Statement 53
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n4:janzz_glossary_search n5:
rdf:object
The system of JANZZon! (the organization of concepts) follows logical criteria, but is also strongly content-driven, focusing on the content of the particular concepts. Background knowledge to the individual terms (their specific content) and the respective indexing of the concepts in the ontology are crucial, because a machine can only “learn” about terms and their significance by the availablilty of this knowledge. Occupations and functions can be organized relatively easily following logical criteria. Hierarchies are rather clear and the structuring of branches is not very complicated. Occupations can therefore be classified and indexed according to different industries and especially existing (international) occupation classifications. Somewhat more complicated to organize are the specializations and skills. A strict logical order is often difficult or not possible at all. For indexing and organizing in the ontology, a specific skill, specialization and the person holding this skill or specialization is the focus and starting point. Example Microsoft Word is clearly related to the concept Microsoft Office, a software. But, Microsoft Word is also often associated with Text processing, still it does not necessarily make sense to subordinate Microsoft Word Text processing. In order that the machine is still able to establish the connection between Microsoft Word and Text processing, both concepts can be linked to each other through relations.
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Embedded HTML5 Microdata Statement 54
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Embedded HTML5 Microdata Statement 52
pwdr:describedby
n4:janzz_glossary_search n5:
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JANZZon! (system)
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schema:headline
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n2:17af4e3993f01acc34d107c335e148109f20ab28