Slides from the evopat ISWC2010 Talk

3. Example

5. Pattern Classification & Survey

9. Steady process of Evolution in Knowledge Bases By petercat.harris@flickr

11. Steady process of Evolution in Knowledge Bases

12. Can we manage this process? By MyMeltingBrain@flickr

14. He uses tags to describe special qualities (not covered by his schema) By pamilne@flickr http://db.caucasus-spiders.info

16. Now Steve wants to extend his vocabulary for these tags

17. That's evolution! By pamilne@flickr http://db.caucasus-spiders.info

19. Code Smells By helder@flickr

21. Works on data and schema level

26. Conceptual Model

27. Conceptual Model

28. Example “ Please set the language to X for all literals which do not have a language tag yet.” lang type : LANG s type : TEMP p type : TEMP ltrl type : TEMP SELECT DISTINCT * WHERE { %s% %p% %literal%. FILTER ( isLiteral(%literal%) ) FILTER ( lang(%literal%) = '' ) } INSERT: %s% %p% setLanguage(%literal%,%lang%) DELETE: %s% %p% %literal% V S U

30. Execute query lang = en type : LANG s type : TEMP p type : TEMP ltrl type : TEMP SELECT DISTINCT ?s ?p ?ltrl WHERE { ?s ?p ?ltrl . FILTER ( isLiteral( ?ltrl ) ) FILTER ( lang( ?ltrl ) = '' ) } INSERT: %s% %p% setLanguage(%literal%,%lang%) DELETE: %s% %p% %literal% V S U

32. Execute pre-processor functions

33. Execute queries lang = en type : LANG s type : TEMP p type : TEMP ltrl type : TEMP SELECT DISTINCT ?s ?p ?ltrl WHERE { ?s ?p ?ltrl . FILTER ( isLiteral( ?ltrl ) ) FILTER ( lang( ?ltrl ) = '' ) } INSERT: %s% %p% setLanguage(%literal%,%lang%) (e.g.: foaf:Person rdfs:label 'person'@en ) DELETE: %s% %p% %literal% (e.g.: foaf:Person rdfs:label 'person' ) V S U

36. Instance and data level Example “ Please create foaf:name values (if not exist) from the corresponding first-name and surname values.”

38. Instance and data level

39. Entity level

40. Syntactic level Example “ Please set the language type 'en' to all literal values of this property which does not have a language tag yet.”

45. Combinatorial analysis

48. Combinatorial analysis

49. Interviews and retrospective coverage checks By pamilne@flickr

52. Combinatorial analysis

60. Execution Engine

61. Starter

65. A Linked Data Archive of common Evolution Pattern

66. An implementation based on our Semantic Data Wiki OntoWiki

68. Modularity of descriptions

69. Performance scales with the maturing of triple stores

70. Expressiveness scales with the maturing of the SPARQL standards

72. Representation of queries could be improved (spinrdf.org Fürber & Hepp @ BIS2010) By stuckincustoms@flickr