Difference between revisions of "Detecting patterns in ontology usage"

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{{ProjectProposal
 
{{ProjectProposal
 
|title=Detecting patterns in ontology usage
 
|title=Detecting patterns in ontology usage
|image=
 
 
|description=When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. Foaf or Dublin Core) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as http://watson.kmi.open.ac.uk/ and http://sindice.com/), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
 
|description=When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. Foaf or Dublin Core) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as http://watson.kmi.open.ac.uk/ and http://sindice.com/), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
 
|tutor=DavideEynard;DavidLaniado;RiccardoTasso;MarcoColombetti
 
|tutor=DavideEynard;DavidLaniado;RiccardoTasso;MarcoColombetti
|cfumin=5
 
|cfumax=20
 
 
|studmin=1
 
|studmin=1
 
|studmax=2
 
|studmax=2
 +
|cfumin=5
 +
|cfumax=20
 
|resarea=Social Software and Semantic Web
 
|resarea=Social Software and Semantic Web
 
|restopic=Semantic Annotations
 
|restopic=Semantic Annotations
 
|level=Ms
 
|level=Ms
|type=Course;Thesis
+
|type=Course; Thesis
|status=Proposal
+
|status=Active
 
}}
 
}}
 
 
When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. [http://www.foaf-project.org/ Foaf] or [http://dublincore.org/ Dublin Core]) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as [http://watson.kmi.open.ac.uk/ Watson] and [http://sindice.com/ Sindice]), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
 
When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. [http://www.foaf-project.org/ Foaf] or [http://dublincore.org/ Dublin Core]) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as [http://watson.kmi.open.ac.uk/ Watson] and [http://sindice.com/ Sindice]), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
  
 
;Tools and instruments
 
;Tools and instruments
 
:ontologies are described in (OWL/)RDF. Student(s) should be able to deal with Semantic Web technologies and libraries.
 
:ontologies are described in (OWL/)RDF. Student(s) should be able to deal with Semantic Web technologies and libraries.

Revision as of 09:26, 27 May 2010

Title: Detecting patterns in ontology usage
Description: When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. Foaf or Dublin Core) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as http://watson.kmi.open.ac.uk/ and http://sindice.com/), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
Tutor: DavideEynard (eynard@elet.polimi.it), DavidLaniado (david.laniado@gmail.com), RiccardoTasso (tasso@elet.polimi.it), MarcoColombetti (colombet@elet.polimi.it)
Start: Nowwarning.pngThe date "Now" was not understood.
Students: 1 - 2
CFU: 5 - 20
Research Area: Social Software and Semantic Web
Research Topic: Semantic Annotations
Level: Ms
Type: Course, Thesis
Status: Active

When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. Foaf or Dublin Core) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as Watson and Sindice), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.

Tools and instruments
ontologies are described in (OWL/)RDF. Student(s) should be able to deal with Semantic Web technologies and libraries.