Presentation of Bio2RDF Cognoscope on 8 Febuary 2010 at BioHackathon 2010 http://hackathon3.dbcls.jp/

1. Bio2RDF Cognoscope A killer app for the life scienc e François Belleau

3. What is RDF ?

4. The vision

5. What is know about hexokinase ?

6. A new approche: The Cognoscope

7. http://www.pcworld.idg.com.au/article/132245/berners-lee_seeks_killer_app_semantic_web "Similarly, if we could get critical mass in life sciences, if we get a half a dozen or a dozen set of ontologies, the core ones for drug discovery out there, then suddenly the Semantic Web within life sciences would have a critical mass. It'll snowball much more rapidly and it will be copied. Other areas will realize: Oh it's worth investing in this," Tim Berners-Lee WWW inventor

8. The problem: How to do data integration in Bioinformatics ? Carole Goble (ISWC 2005)

9. http://www.biopax.org/Docs/2004-10-28_SWLS-SessionVII.pdf

10. Tokyo subway map

11. Montreal subway map

12. http://informationarchitects.jp/ia-trendmap-2007v2/ Web Trend Map 2007

13. The proposed solution Bio2RDF solve the problem of data integration in bioinformatics by applying the Semantic Web approach based on RDF, OWL and SPARQL technologies.

14. Web of data subway map from W3C http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/#(1)

15. Bio2RDF inspiration in 2005

16. What is RDF ?

17. "Wouldn't it be great if you were able to organize all this information based on your own terms, instead of based on the application you use to access the information ?” Ramanathan V. Guha RDF initiator http://cgi.netscape.com/columns/techvision/innovators_rg.html

18. R esource D escription F ramework

19. It is triples... < subject > < predicate > < object_uri > . OR < subject > < predicate > &quot; object_literal &quot; .

20. A triple

21. The same in RDF/XML <?xml version=&quot;1.0&quot;?> <rdf:RDF xmlns:rdf=&quot;http://www.w3.org/1999/02/22-rdf-syntax-ns#&quot; xmlns:exterms=&quot;http://www.example.org/terms/&quot; > <rdf:Description rdf:about=&quot; http://www.example.org/index.html &quot;> < exterms:creation-date > August 16, 1999 </ exterms:creation-date > </rdf:Description> </rdf:RDF>

22. The same in NTRIPLES < http://www.example.org/index.html > < http://www.example.org/terms/creation-date > “ August 16, 1999 ” .

23. It is a technology stack http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/

24. It is a distributed architecture http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/

25. Goal #1 Convert many public bioinformatic databases to RDF.

26. Bio2RDF rdfised public databases

27. Bio2RDF first map in 2007

28. Bio2RDF Mouse and Human Atlas map in 2008 65 millions triples

29. Linked Data cloud evolution http://linkeddata.org/ http://esw.w3.org/topic/TaskForces/CommunityProjects/LinkingOpenData/DataSets/Statistics Linked data cloud in March 2009 Linked data cloud in May 2007

30. http://www.ted.com/talks/tim_berners_lee_on_the_next_web.html

31. LODD wins the 2009 Triplify challenge http://triplify.org/files/challenge_2009/LODD.pdf

32. Bio2RDF cloud map of namespaces from 2,3 billions triples

33. How we did it ?

34. http://www.w3.org/DesignIssues/LinkedData

35. http://bio2rdf.wiki.sourceforge.net/Banff%20Manifesto

36. Bio2RDF realtime rdfiser in 2007

38. Virtuoso SPARQL endpoints network

39. Namespace resolution through DNS subdomain

40. Bio2RDF has 3 mirror sites http://cu.bio2rdf.org/ http://qut.bio2rdf.org/ http://quebec.bio2rdf.org/

43. http://bio2rdf.org/searchns/ ns / searchedTerm

44. Goal #2 Ask a useful question to the network of SPARQL endpoints.

45. What is known about hexokinase ?

46. Existing integrated search services NCBI/Entrez EBI/EB-eye KEGG/DBGET Riken/OmicScan

47. Ask http://atlas.bio2rdf.org/fct

48. Submit a SPARQL query http://atlas.bio2rdf.org/sparql

49. Ask it to each SPARQL endpoint http://NAMESPACE.bio2rdf.org/fct

50. Ask Bio2RDF REST federated search http://bio2rdf.org/search/hexokinase

51. Or use the Cognoscope...

52. The mashup principle To answer a complex question we first need to build a specific database, a mashup, to which we submit the appropriate query.

56. The filtering effect is based on the inherent semantic of RDF graph described using types and predicates.

57. Facet browsing is used to zoom in and out in the observed graph.

58. Full text search is used to discover concept.

60. Bio2RDF Cognoscope architecture Linked Data cloud of SPARQL endpoints Triplestore Virtuoso 6 Workflow engine Taverna 2.1

62. Identify the needed namespaces and split the query to fetch each data source separetly

63. Build a mashup using a Taverna workflow that instanciate a local triplestore

64. Execute your complex query locally on the mashup

65. The SPARQL query needed (dont try this home, do it on the web !)

66. Bio2RDF Cognoscope using Taverna 2.1

67. Cognoscope query for What is known about hexokinase ?

68. Et voilà !

69. Where to get Bio2RDF Cognoscope http://www.myexperiment.org/search?query=cognoscope

70. Bio2RDF SPARQL endpoints http://delicious.com/tag/bio2rdf:sparql

72. Dumontier Lab

75. Michel Dumontier

76. Peter Ansell

77. Can you help ?