Phil Ashworth and Dean Allemang, "Building a semantic integration framework to support a federated query "

1. Building a semantic integration framework to support a federated query environment in 5 steps Philip Ashworth UCB Celltech Dean Allemang TopQuadrant

3. Data Integration… Problems Warehouse DB Project DB Project Marts Applications App DB App DB’s App DB’s Registration, Query DI, Query DI Query DI App DB’s

5. Data Integration… Thoughts Data Integration is clearly evolving But it is not fulfilling the needs If we identify the need… can we see what we should be doing?

6. Accessible Data True Integration Variety of Sources Align Concepts Data has Context All Data for All Projects Data Integration… Needs

7. Data Integration… There is a way! Open Linked Data Cloud Connected and linked data with context Created by a community Significant linking hubs appearing Significant scientific content A Valuable resource that will only Grow! Something we can learn from!

8. Data Integration… Starting an Evolutionary Leap No one internally really knows about this Can’t just rip and replace old systems Have to do some ground work

10. Linked Data… The Quest Highly Repetitive & Promiscuous Highly Promiscuous & Repetitive

12. Rest Services (Abstraction layer) Semantic Integration Framework Knowledge Collation, Concept mapping, Distributed Query Result inference, Aggregation Increasing Ease of Development Decreasing knowledge of Semantic technologies The Idea Applications Business Process / Workflow Automation PURL Data Sources RDBMS Oracle,Postgres SQL, mySql RDF Triple Store MS Excel TXT Doc RDF Sparql EndPoint Sparql EndPoint Native

16. Rest Services (Abstraction layer) Semantic Integration Framework Knowledge Collation, Concept mapping, Distributed Query Result inference, Aggregation Applications Business Process / Workflow Automation PURL RDF Data Sources Understand Data Sources (concepts, access, props) Understand Links Across Sources Automate some tasks Accessible Via Services Easy to wire up Understand UCB concepts Understand how UCB Concepts fit with source concepts Step 2: Integration Framework

18. Step 2: Integration Framework. DB1 Dataset Ontology (VoID) UCB Concept Ontology (SKOS) Integration Framework Sem Int Framework narrowMatch UCB:Antibody DB1:Antibody UCB:Person DB1:User narrowMatch narrowMatch UCB:Project DB1:Project

19. Step 2: Integration Framework. DB1 Dataset Ontology (VoID) UCB Concept Ontology (SKOS) DB2:Person UCB:Person DB1:User DB3:Employee DB2 DB3 DB3:Contact Sem Int Framework narrowMatch narrowMatch narrowMatch narrowMatch

20. Step 2: Integration Framework. DB1 Dataset Ontology (VoID) UCB Concept Ontology (SKOS) DB2:Person UCB:Person DB1:User DB3:Employee DB2 DB3 DB3:Contact Person_DB1_DB2 Person_DB1_DB3 Linksets Sem Int Framework narrowMatch narrowMatch narrowMatch narrowMatch

21. Step 2: Integration Framework. Dataset Ontology (VoID) UCB Concept Ontology (SKOS) Sem Int Framework 2 3 1 10 7 4 8 5 9 6 12 11

23. Step 3: Rest Services Dataset Ontology (VoID) UCB Concept Ontology (SKOS) DB2 DB3 Keyword Search Get Info Find UCB:Person “phil” Search DB1:User Tell me the sub-types of UCB:Person Here are the resources for “phil” ldap:U0xx10x, itrack:101, moc:scordisp etc…. Search DB3:Employee Search DB3:Contact Search DB2:Person Rest Services Can the linksets tell us any info? Tell me the datasets for the sub-types DB1

24. Step 3: Rest Services Dataset Ontology (VoID) UCB Concept Ontology (SKOS) Keyword Search Get Info Tell me the super-types of all resources Retrieve DB1:U0xx10x Tell me about moc:scordisp Here is everything I know about it. DB2 DB3 Retrieve DB2:scordisp Retrieve DB3:philscordis Tell me everything about this resource? Rest Services DB1

26. Step 4: Data Exploration UCB Concepts Search submitted to “Keyword Search” Service Applications

27. Step 4: Data Exploration Results Displayed. Index shows inference is already taking place Applications

28. Step 4: Data Exploration Drag Instance to basket, Initiates “Get Info” Service call Applications

29. Step 4: Data Exploration Select Instance Data Displayed per Source Applications

30. Step 4: Data Exploration Links to other data items Applications

31. Step 4: Data Exploration Displays Sparse data Submit Instance to“Get info” service Applications

32. Step 4: Data Exploration More Detailed Information Applications

33. Step 4: Data Exploration He has another interaction. Lets Explore. Applications

34. Step 4: Data Exploration Applications

35. Step 4: Data Exploration Applications Data cached as we navigated Concept Explorer. Can now be investigated.

36. Step 4: Data Exploration Structure concept Keyword Search pulls data from internal and external data sources Add to basket After detailed Information retrieved a second Structure has been identified without a keyword search Integrated Internal and External data Applications

37. Step 4: Data Exploration Applications

40. Step 4: Knowledge Base Semantic Integration Framework Keyword Search Get Info Data Sources App Service “ Tell me about the protein with Gene ID X ” and I want to know about Literature Refs , Sequences , Descriptions, Structure …… etc. Applications

41. Step 4: Knowledge Base Applications

42. Step 4: Knowledge Base Applications

43. Step 4: Knowledge Base Applications

44. Step 4: Knowledge Base Applications

45. Step 4: Knowledge Base Applications

49. Questions?