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Semantic Frameworks, General Concept

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By Looking at several Semantic Frameworks, General Concept of Semantics and specifically the RedLand Framework the following Notes were made.

The basic workflow is like this:

  1.  Analysis of a Structured or Unstructured Document
  2. Result of the Analysis is a Formatted Data Tree
  3. Two Datatrees are then compared and later associated with each other, using Semantic Logic. The Result is a Tripple.

Extracting Content from an HTML Page or Tag Soup

Redland allows you to extract a Information Tree from a Unstructred Dataformat.
Where you got a HTML Page, Valid or Tag Soup, the parser extracts all type of defined Data.

The Exractor is designed for eRDF, RDFa, the core 15-20 microformats, OpenID hooks, basic Dublin Core, and other formats (and mappings)
Many formats don’t necessarily map to a single RDF vocabulary, e.g. a social graph aggregator might prefer FOAF as the target format, an address book application may be based on a certain vCard-RDF mapping. Additionally, only a subset of all possible triples in a document will be needed in a given context.

It was designed for parsing and serializing RDF/XML files. Later it evolved into a more complete framework with storage and query functionality.
Even tough its not developed anymore, Arc2 is the most-installed RDF library.

See also:
https://github.com/semsol/arc2/wiki/Extracting-RDF-from-HTML

Some Interesting Ressources are:
http://librdf.org/using.html
http://www10.org/cdrom/papers/490/
http://librdf.org/
http://journal.dajobe.org/journal/

Author: Guntram Bechtold

Produkte von der ersten Idee zur fertig Lösung zu bringen ist zentrale Aufgabenstellung von Bechtold. “Als Industrial Designer finde ich es absolut spannend wie die Produkte der Digitalisierung unsere Welt gestalten. Wissen und Kreativität so zu kombinieren dass nachhaltiger Nutzen für Anwender und Unternehmen entsteht ist entscheidend”. Als #Certified Scrum Master hat Bechtold sich auf die Planung und Umsetzung von innovationsgetriebener Geschäftsmodellen spezialisiert.

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