Exploring and using the Semantic Web - SSSW09 tutorial
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This document discusses exploring and using the Semantic Web. It provides examples of querying DBPedia to find information and describes several tools for exploring the Semantic Web including semantic search engines, APIs, datasets, and applications that have been built using Semantic Web resources. The document emphasizes that while much information is available, there is still work to be done in improving links between resources and understanding relevance and relations within the Semantic Web.
Exploring and using the Semantic Web - SSSW09 tutorial
- 1. Exploring and Using the Semantic Web Mathieu d’Aquin KMi, The Open University – [email protected]
- 2. Exploring the Semantic Web What?? RDF documents Ontologies Vocabularies Linked Data
- 3. Example: Exploring DBPedia “ DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link other data sets on the Web to Wikipedia data.” -- http://wiki.dbpedia.org/About Provides a huge, multi-domain knowledge base, accessible through the Web, using Semantic Web standards, mainly SPARQL ( http://dbpedia.org/sparql ) Example: “what are the names of German musicians who were born in Berlin?” PREFIX dbo: http://dbpedia.org/ontology/ SELECT ?name WHERE {?person dbo:birthplace <http://dbpedia.org/resource/Berlin>. ?person skos:subject <http://dbpedia.org/resource/ Category:German_musicians>. ?person foaf:name ?name . }
- 4. Example: Exploring DBPedia “ DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link other data sets on the Web to Wikipedia data.” -- http://wiki.dbpedia.org/About Provides a huge, multi-domain knowledge base, accessible through the Web, using Semantic Web standards, mainly SPARQL ( http://dbpedia.org/sparql ) Example: “what are the names of German musicians who were born in Berlin?” PREFIX dbo: http://dbpedia.org/ontology/ SELECT ?name WHERE {?person dbo:birthplace <http://dbpedia.org/resource/Berlin>. ?person skos:subject <http://dbpedia.org/resource/ Category:German_musicians>. ?person foaf:name ?name . } Alexander Marcus, Klaus Voormann
- 5. Linked Open Data (LOD) cloud: http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
- 6. Other Tools to Explore the Linked Data Cloud… Instance of OpenLink Virtuoso on amazon EC2 loaded with data from the LOD cloud And also semantic web browsers such as Tabulator, RKBExplorer, etc. But… the LOD cloud is not everything… Many ontologies, vocabularies and datasets of various sizes and complexities are being created all the time
- 7. Finding Semantic Information on the Web With Semantic Web Search Engines Sindice: http://sindice.com Watson: http://watson.kmi.open.ac.uk Swoogle: http://swoogle.umbc.edu/ Falcons: http://iws.seu.edu.cn/services/falcons/objectsearch/ SWSE: http://swse.deri.org/ …
- 9. Example: Watson (interface) http://watson.kmi.open.ac.uk
- 10. So, what can you find on the Semantic Web? Size: LOD Cloud: 4,5 Billion Triples (estimated) Sindice: claim 54.65 million documents (June 2009) An analysis of a sample of the Watson collection (not up to date!): Language Complexity Size of documents Topic coverage
- 11. Using It How?? Building Applications!!! Reusing in Ontologies Linking to Other Datasets Through SPARQL Through API
- 12. What to use? SPARQL endpoints, and such… DBPedia’s SPARQL endpoint Virtuoso LOD instance All other LOD nodes The Talis Platform Etc. Semantic Web search engines services and APIs Watson: complete, open SOAP and REST API, with Java client Sindice: REST API for entity lookup, etc. Swoogle: simple search REST API Falcons: simple search REST API SWSE: SPARQL endpoint! Other nice (online!) tools: OpenCalais Semantic Proxy : for entity recognition and annotation in web pages Textwise SemanticHacker : for document classification Triplify, D2R, etc.: for transforming databases into semantic web resources …
- 13. Example: Watson API Provide Semantic Web application developers with the ability to efficiently: Locate (find) Semantic Web documents online using advanced search functions Explore the documents, automatically extracted metadata and content Query the documents, to exploit online knowledge in an homogeneous way In a set of lightweight APIs, and without having to download the data or use any other dedicated infrastructure.
- 14. Some applications we developed Ontology Reuse: The Watson Plugin Question Answering: PowerAqua Semantic Browsing: PowerMagpie Semantic Relation Discovery: Scarlet Folksonomy Enrichment And also: Word sense disambiguation Query Expansion Synonym Discovery…
- 15. A demonstrator: Wahoo! Find on the Semantic Web terms to specialize or generalize a query to a search engine (Yahoo).
- 16. The technical stuff… Find ontologies containing the keyword “researcher” http://watson.kmi.open.ac.uk/API/ semanticcontent/keywords? q= researcher … exactly “researcher” in the label or id of a class http://watson.kmi.open.ac.uk/API/ semanticcontent/keywords?q= researcher &scope= LN+Label &ent= Class &match= Exact Find entities corresponding to “researcher” in ontology http://watson.kmi.open.ac.uk/API/ entity/keyword?q= researcher & uri= http://calo.sri.com/core-plus-office &scope= LN+Label &ent= Class &match= Exact Find subclasses and superclasses of an entity http://watson.kmi.open.ac.uk/API/ entity/subclasses? ent=http://calo.sri.com/core-plus-office#Researcher &uri= http://calo. sri.com/core-plus-office The rest is interface stuff and call to Yahoo!
- 17. Other Example: Scarlet ka2.rdf Researcher AcademicStaff Semantic Web Researcher AcademicStaff ISWC SWRC Ham SeaFood Semantic Web Ham SeaFood Meat Meat SeaFood Agrovoc NALT pizza-to-go wine.owl NALT
- 19. Other Example: The Watson Plugin Chose an entity to search Get entities from online ontologies Integrate statements Into the edited ontology
- 20. More? Exploring, using… and contributing to the Semantic Web! Cupboard: an ontology hosting system http://cupboard.open.ac.uk Using semantic web resources to improve the quality on the Semantic Web. Manual rating of ontologies, trust network between ontologies and ontology providers, improving links between ontologies and datasets through reuse. A lot left to do! Understanding the notions of relevance of Semantic Web information, of agreement between ontologies… Detecting and managing the relations between ontologies. Making the network of resources explicit…
- 21. Thanks! Hands-on session this afternoon Using Semantic Web search engines Using Semantic Web APIs Building ontologies by reuse Publishing an ontology with Cupboard Now: questions? Comments? Other topics of interest? Contact: [email protected]