2. Only first semantic applications
Mostly research or proof of concepts
Few semantic applications
Domains
Biology
Biomedicine
semantic content management
fewer semantic products
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3. Example: Semantic Information Integration
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Example: Semantic Information Integration
views
integration ontology
manual mappings
data source ontologies
automatic mappings
data sources
<article>
<articleid>a-5634</articleid>
<category>printer</category>
<name>hp81</name>
<price currency=‘USD’>500</price>
<producer>hp</producer>
<resolution>1960 dpi</resolution>
<type>laser</type> ….
</article>
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4. Some Problems Complicated semantic technology stack Many technologies
E.g OWL on RDF
Partially semantically
Complicated syntactically
Many technologies
Logic programming
OWL
Rules
Triples: RDF
SQL-like: SPARQL
Grammer-oriented XML schema
Hierarchies: XML
Functional programming
XQuery
Need for Stability and Scalibility
Problems for wider adoption
Only explainable to partial experts
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5. What is convincing Executable models
Usage in more restriced enterprise context
Processing meta information
Urgent need to process semantic in applications
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