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-K.Venkat

Position Paper - Relational.OWL Vs Ontology-based Framework for Integrating Databases into the Semantic Web. -K.Venkat. Agenda. About semantic Web Making relational database compatible to semantic web SPARQL and Relational.OWL Ontology based framework OntoGrate Engine

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-K.Venkat

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  1. Position Paper - Relational.OWL Vs Ontology-based Framework for Integrating Databases into the Semantic Web -K.Venkat

  2. Agenda • About semantic Web • Making relational database compatible to semantic web • SPARQL and Relational.OWL • Ontology based framework OntoGrate Engine • Contrasting two approaches • Position

  3. Semantic Web • Technology allows the data to be shared among different data source. • Semantic web integrates data from different data sources. • Integrating is done through relation between the two data[6].

  4. Two semantic web technologies are OWL and RDF • OWL and RDF are the standards for representing data in the semantic web • OWL is Ontology language that defines frame work to combine different domains • RDF for the merging different data source.

  5. Relational.OWL and SPARQL • Relational.OWL represents the relational schema in the ontology language. SPARQL for querying • Relational.OWL defines different classes corresponds the each elements in the data schema • Data is represented as instance of classes [2]

  6. Cont.. • SPARQL performs most of the basic operations that can be performed using the SQL • Joint operation performed by the SPARQL is shown below • <http://example.org/book/book1> <http://purl.org/dc/elements/1.1/title> ?title

  7. Ontology based frame work: • The data form the relational table are converted to ontology language using Web-PDDL • Ontograte engine integrates data that are represent in WEB-PDDL • Web-PDDL is converted to OWL first using the PDDOWL • It also converts the queries represented in semantic language to SQL • OWL-QL to PDDSQL using PDDOWL and PDDSQL to SQL using PDDSQL translators.

  8. The Ontograte architecture consists of different blocks [1] • Integration of schemas and ontology • Matching generation • Learning mapping form the knowledge module • User interface • Inference engine

  9. Contrasting SPARQL/ Relational.OWL and ontology based framework • Ontology based onto concentrates more on data integration • SPARQL is new query language and misses some functions such as grouping. • OntoGrate engine is integrated frame work with translators and good user interface. • Complex subclasses makes the Relational.OWL complex. • The relational.OWL don’t need transfer. SPARQL need the data to be in the RDF • SPARQL is still in the research stage even though it has some advantages, Ontograte Engine have advantage. • SPARQL query language used in the first approach is relative new query language and it doesn’t fully support all the functions such as grouping, sub Queries etc of SQL [2].

  10. SPARQL is a semi structured and does not require joints because mapping can be done using relationship between the data that is represented in RDF format It also does not support hierarchal queries directly [8]. • Though we need transfer in OntoGrate engine it takes around 3 seconds for 1000 records of data [1], which is relatively fast.

  11. Conclusion • The SPARQL query language is relative new, though it has some advantages it is better to go for Ontograte which uses SQL and also it is integrated framework which is experimented. Even though we need target data source and manual update we can go for OntoGrate engine.

  12. References: • Dejing Dou, Paea LePendu, Shiwoong Kim and Peishen Qi, “Integrating Databases into the Semantic Web through an Ontology-based Framework”, ICDEW, p. 54, Proceedings of the 22nd International Conference on Data Engineering Workshops (ICDEW'06), Year of Publication: 2006. • Cristian P´erez de Laborda, Stefan Conrad, “Bringing Relational Data into the Semantic Web using SPARQL and Relational.OWL”, ICDEW, p. 55, 22nd International Conference on Data Engineering Workshops (ICDEW'06), 2006. • Janet Daly, “World Wide Web Consortium Issues RDF and OWL Recommendations”, http://www.w3.org/2004/01/sws-pressrelease . • Eric Prud'hommeaux, Andy Seaborne, “SPARQL Query Language for RDF”, http://www.w3.org/TR/rdf-sparql-query/. • Eric Prud'hommeaux, Andy Seaborne, “SPARQL Query Language for RDF”, W3C Working Draft 21 July 2005, http://www.w3.org/TR/2005/WD-rdf-sparql-query-20050721/#QueryForms. • “Semantic Web”, http://www.w3.org/2001/sw/. • Csongor Nyulas, Martin O’Connor, Samson Tu, “Data Master – a Plug-in for Importing Schemas and Data from Relational Databases into Protege, http://protege.stanford.edu/conference/2007/presentations/10.01_Nyulas.pdf. • Lee Feigenbaum, “SPARQL FAQ”, http://thefigtrees.net/lee/sw/sparql-faq.

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