1. Dr. Jim Bowring Computer Science Department College of Charleston CSIS 690 (633) May Evening 2009 Semantic Web Principles and Practice Class 4: 20 May 2009

2. Class 4: Roadmap Announcements and Assignments Questions SWP Chapter 3 (cont) SWWO Chapter 4

3. SW Application Architecture How do we put the SW to work? RDF Parser / Serializer RDF Store (triple store) RDF Query Engine Application

4. RDF Parser / Serializer Starting with set of triples, serialize to a format (.rdf) parse the serialized file return to original set of triples Starting with serialized triples parse the serialized file (.rdf) serialize to a format (.rdf) ==> no guarantee.rdf files are identical

5. Converters and Scrapers Converters produce.rdf from spreadsheets, RDBs, etc. Scrapers: HTML pages are structured without RDF info Solvent of Simile project = FF extensionSolvent used with PiggyBankPiggyBank Scrapers: HTML pages with RDF info Microformats (see Google and RDFa)see Google and RDFa GRDDL W3C (Gleaning Resource Descriptions from Dialects of Languages) RDFa: use attribute tags in HTML to embed info

6. RDF Store Includes parser serializer query engine scripting language support merging capabilities T1 + T2, where identical URIs are == Triples can be stored in a regular relational database and accessed with SQL Optimization is an open question

7. Data Standards / Interoperability Historically, RDBs’ data are not interchangeable without human intervention RDF stores’ data ARE ! (standards) Competition is based on scalability, performance, etc.

8. RDF Query Engines and SPARQL SPARQL is W3C standard SPARQL ‘SELECT’ Query based on triple pattern use N3 format of s p o. where any of s, p, o can be ?var or graph pattern {s1 p1 o1. s2 ps o2.} where any ?var is assumed to be bound UNIONs supported SELECT ==> a table or SPARQL Query Results XML Format

9. SPARQL CONSTRUCT Produces new graph from two input graph patterns (see explicit reification example) CONSTRUCT {?s ?p ?o} WHERE {?r rdf:subject ?s. ?r rdf:predicate ?p. ?r rdf:object ?o. web:Wikipedia m:says ?r.} SPARQL can query other data sources (wrapped)

10. SPARQL vs. Relational Queries SPARQL queries similar to predicate calculus (AND, OR, NOT, EXISTS, FORALL …) recursive, with no sub-queries or self-joins Different vendors implement SPARQL in different ways

11. Application Code Calendar integration Map integration Annotation Content Management MashUps Application federates and merges results into a single graph (triples) for use such as in a dynamic SW RDF-backed portal See: http://drupal.org/http://drupal.org/

12. Data Federation Designed into RDF data model Separation of concerns: federate first query second Therefore a query operates seamlessly over multiple data sources without knowing the origins of the data