Semantic web for ontology chapter4 bynk
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Chapter 4 discusses the structure of semantic web applications, focusing on key components such as RDF stores, RDF parsers/serializers, and SPARQL query engines. It explains how RDF data can be easily managed and transferred between systems, highlighting the importance of RDF's flexible data model and interoperability. Additionally, it covers the basics of constructing SPARQL queries, including the use of triple patterns and graph patterns.
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Semantic web for ontology chapter4 bynk
- 1. Chapter 4 Semantic Web Application Structure By NK
- 2. Keyword • RDF store • RDF query engine • SPARQL • SPARQL endpoint • Application interface • Scraper • Converter • RDFa & GRDDL
- 3. Context • RDF Parser / Serializer • RDF Store
- 4. RDF Parser / Serializer ( 1 ) • RDF Parser – can read RDF Application’s data source that has .rdf extension. – has a data source as an Input data. – translate data source into triple
- 5. RDF Parser / Serializer ( 2 ) • Serializer – It is a Reverse Operation – Using a RDF parser and Serializer to possible the 'Round-trip' of the triple. – What mean is ‘Round-trip’?
- 6. RDF Parser / Serializer ( 3 ) • Example for Serializer Format – N-Triples
- 7. RDF Store ( 1 ) • Store RDF Data • Using each parser and serializer for ‘Populate’ and ‘Publish’ • In contrast to a relational data store, includes as a fundamental capability the ability to ‘merge’ two data sets together – Because of Flexible nature of the RDF data model.
- 8. RDF Store ( 2 ) • RDF Data Standards and Interoperability of RDF Stores – Relational data store is a difficult process to transfer a whole database from one system to another. – But RDF data model is a shared by all of these products – All of them can import and export their data sets in the RDF/XML format. – This feature, early and aggressive standardization process, makes it much easier to begin with one RDF store, secure in the knowledge that the system can be migrated to another as the need arises.
- 9. RDF Store ( 3 ) • RDF Query Engines and SPARQL – Accessed using a query language. – Cover the highlights of SPARQL query language in this section.
- 10. RDF Store ( 4 ) • RDF Query Engines and SPARQL N3 Graph
- 11. RDF Store ( 5 ) • RDF Query Engines and SPARQL – The basic building block of a SPARQL query is the triple pattern. – Variables are indicated as symbols preceded by the special ‘?’ character. – Example • ?w lit:wrote lit:KingLear . lit:Shakespeare ?r lit:KingLear. lit:Shakespeare lit:wrote ?p.
- 12. RDF Store ( 6 ) • RDF Query Engines and SPARQL – Who wrote King Lear? – What relationship did Shakespeare have to King Lear? – What did Shakespeare write?
- 13. RDF Store ( 7 ) • RDF Query Engines and SPARQL – Interesting query is one in which the query specifies a graph pattern. – A graph pattern is specified as a set of triple patterns, with the stipulation that any variable that appears in two or more triple patterns must match the same resource in the graph. – In SPARQL syntax, graph patterns are given as a list of triple patterns enclosed within braces ({ and }).
- 14. RDF Store ( 8 ) • RDF Query Engines and SPARQL – ?person lit:wrote lit:KingLear .} {?person bio:livedIn ?place. ?place geo:isIn geo:England. ?person lit:wrote lit:KingLear . }
- 15. RDF Store ( 8 ) • RDF Query Engines and SPARQL – It has no knowledge that marriage is a symmetric union and so Shakespeare must have married Anne Hathaway. – Solution OWL (Will Learn Chapter 7)
- 16. Summary • What are RDF Parser and Serializer • How operation RDF Store • How access RDF Store using RDF Query engine • SPARQL • SPARQL endpoint