An RDF Data Model for the Semantic Web. 5 th Oracle Life Sciences User Group meeting May 16-17, 2005

Transcription

1

2 An RDF Data Model for the Semantic Web 5 th Oracle Life Sciences User Group meeting May 16-17, 2005

3 Agenda Introduction 5 min Susie Stephens Semantic Web for Life Sciences 25 min Susie Stephens Oracle support of RDF in RDBMS 25 min Souripriya Das Demo of Siderean s Seamark Navigation Server 25 min Mike DiLascio, David LaVigna & Joanne Luciano Discussion 10 min Susie Stephens

4 Semantic Web for Life Sciences Susie Stephens

5 What is the Semantic Web? A machine-readable format that is Web compatible The Semantic Web adds definition tags to information in Web pages Enables computers to discover data more effectively Allows new associations to form between pieces of information

6 Resource Description Framework W3C standard for the common data format Based on triples (subject predicate object) Everything has a URI Ontologies used to label the RDF tagged elements Image Source: W3C

7 Image Source: W3C

8 Enterprise Integration Hub Image Source: W3C

9 Semantic Web Stack Image Source: W3C

10 Pharma Productivity Source: PhRMA & FDA 2003

11 Critical Path Initiative Source: Innovation or Stagnation, FDA Report, March 2004

12 Ontology Frameworks for Integration <hasproduct> Protein Gene <transcribes> <translatesto> <participatesin> <influences> Disease <profiledby> Microarray experiment <probefor> <efficacymarkerfor> mrna <affectedtissue> Drug <targets> <MOA> Treatment <located> Localization Intervention point <affecting> Cascade pathway <druginteraction> <partof> Bio-process Target model

13 Biological Pathways Image Source: Cytoscape

14 Beyond the Dead Graphical Model Image Source: KEGG

15 Assigning Trust Values to Data Image Source: SWANS

16 Inferencing If Gene G is implicated in Disease D, and its Protein Product P is a functional component of only Pathway P2 -> then Disease D directly perturbs Pathway P2 <rdf:description> <log:is rdf:parsetype= Quote > <rdf:description rdf:about= variable#gene_g > <hasproduct rdf:resource= variable#protein_p /> <isimplicatedin rdf:resource= variable#disease_d /> </rdf:description> <rdf:description rdf:about= variable#protein_p > <inpathway rdf:resource= variable#pathway_p2 /> </rdf:description> <log:is> <log:implies rdf:parsetype= Quote > <rdf:description rdf:about= variable#disease_d > <D_perturbs rdf:resource= variable#pathway_p2 > </rdf:description> </log:implies> </rdf:description>

17 Why Semantic Web for Life Sciences? Heterogeneous data integration using explicit semantics Expression well-defined and rich models of biological systems Annotating findings and interpretations formally and sharing with other scientists Embedding models and semantics within papers Applying logic to infer additional insights and to propose and/or capture new hypotheses

18 Q U E S T I O N S A N S W E R S

19 RDF Support in Oracle RDBMS Souripriya Das, Ph.D. Consultant Member of Technical Staff Oracle New England Development Center

20 Overview Three types of database objects Model RDF graph consisting of a set of triples Rulebase Set of (user-defined) rules Rule Index Entailed RDF graph We discuss following aspects for each type of object DDL DML Views Security RDF Query (with Inference)

21 RDF Models

22 Model: Overview Each RDF Model (graph) consists of a set of triples A triple (statement) consists of three components Subject URI or blank node Predicate URI Object URI or literal or blank node A statement itself can be a resource (allowing nested graphs)

23 Model: Example Family: (:John :brotherof :Mary) (:John :age 16 ^^xsd:integer) (:Mary :parentof :Matt) (:John :name John ) (:Mary :name Mary ) Reification: (:John :thinks _:S1) (_:S1 rdf:subject :Sue) (_:S1 rdf:predicate :livesin) (_:S1 rdf:object NYC ) :John age 16 brotherof parentof :Mary :Matt thinks :Sue livesin NYC

24 RDF Query

25 SDO_RDF_MATCH Table Func Arguments Graph pattern A sequence of triple patterns Triple patterns typically use variables RDF Data set a set of models Filter Aliases FROM TABLE(SDO_RDF_MATCH( (?x :brotherof?y) (?y :parentof?z), SDO_RDF_Models( family ), )) t

26 SDO_RDF_MATCH: return Columns (of type VARCHAR2) in each returned row: For each variable?x in Graph Pattern x x$rdfvtyp URI, Literal, Blank node x$rdfltyp Specific literal type (e.g., xsd:integer) x$rdfclob Contains actual value, if?x matches a CLOB value x$rdflang Language tag, if any (e.g., en-us ) If no variable in Graph Pattern A dummy column

27 SDO_RDF_MATCH: matching Matching multiple representations The same point in value space may have multiple representations 10 ^^xsd:integer 10 ^^xsd:positiveinteger 010 ^^xsd:integer ^^xsd:integer SDO_RDF_MATCH automatically resolves these

28 RDF Query: Example Find salary and hiredate of all the uncles SELECT emp.name, emp.salary, emp.hiredate FROM emp, TABLE(SDO_RDF_MATCH( (?x :brotherof?y) (?y :parentof?z) (?x :name?name), SDO_RDF_Models( family'), )) t WHERE emp.name=t.name; Use of SDO_RDF_MATCH allows embedding a graph query in a SQL query

29 RDF Query: Example 2 Find pairs of persons residing at the same address where the first person rents a truck and the second person buys a fertilizer SELECT t3.x name1, t3.y name2 FROM AddrTable t1, AddrTable t2, TABLE(SDO_RDF_MATCH( (?x :rents?a) (?a rdf:type :Truck) (?y :buys?b) (?b rdf:type :Fertilizer), SDO_RDF_Models( Activities'), )) t3 WHERE t1.name=t3.x and t2.name=t3.y and t1.addr=t2.addr;

30 RDF Rulebases

31 Rulebase: Overview Each RDF rulebase consists of a set of rules Each rule consists of antecedent: graph-pattern filter condition (optional) Consequent: graph-pattern One or more rulebases may be used with relevant RDF models (graphs) to obtain entailed graphs

32 Rulebase: Example Rules in a rulebase family_rb: Antecedent: (?x :brotherof?y) (?y :parentof?z) Filter: NULL Consequent: (?x :uncleof?z) Antecedent: (?x :age?a) Filter: a >= 65 Consequent: (?x :agegroup Senior ) Antecedent: (?x :parentof?y) (?y :parentof?z) Filter: NULL Consequent: (?x :grandparentof?z)

33 RDF Rule Indexes

34 Rule Index: Overview A rule index represents an entailed graph A rule index is created on an RDF dataset (consisting of a set of RDF models and a set of RDF rulebases)

35 Rule Index: Example A rule index may be created on a dataset consisting of family RDF data, and family_rb rulebase (shown earlier) The rule index will contain inferred triples showing uncleof and agegroup information

36 RDF Query with Inference

37 SDO_RDF_MATCH with Rulebases Arguments Graph pattern A sequence of triples (with variables) RDF Data set a set of models a set of rulebases Filter Aliases FROM TABLE(SDO_RDF_MATCH( (?x :uncleof?y), SDO_RDF_Models( family ), SDO_RDF_Rulebases ( rdfs, family_rb ) )) t

38 RDF Query w/ Inference: Example Find salary and hiredate of all the uncles SELECT emp.name, emp.salary, emp.hiredate FROM emp, TABLE(SDO_RDF_MATCH( (?x :uncleof?y) (?x :name?name), SDO_RDF_Models( family'), SDO_RDF_Rulebases( rdfs, family_rb'), )) t WHERE emp.name=t.name;

39 RDF Query w/ Inference: Example 2 Find pairs of persons residing at the same address where the first person rents a truck and the second person buys a fertilizer SELECT t3.x name1, t3.y name2 FROM AddrTable t1, AddrTable t2, TABLE(SDO_RDF_MATCH( (?x :rents?a) (?a rdf:type :Truck) (?y :buys?b) (?b rdf:type :Fertilizer), SDO_RDF_Models( Activities'), SDO_RDF_Rulebases( rdfs ), )) t3 WHERE t1.name=t3.x and t2.name=t3.y and t1.addr=t2.addr;

40 RDF Models

41 Model: DDL Procedures provided as part of the API may be used to Create a model Drop a model When a user creates a model, a database view gets created automatically rdfm_family A model corresponds to a column of type SDO_RDF_TRIPLE_S in a base table Each model has exactly one base table associated with it

42 Model: DDL Creating a Model Create an Application Table CREATE TABLE family_table ( id NUMBER, family_triple SDO_RDF_TRIPLE_S); Create a Model EXEC SDO_RDF.CREATE_RDF_MODEL( family, family_table, family_triple ); Automatically creates the following database view rdfm_family ( )

43 Loading RDF Data into Oracle Java API provided to load NTriple into NDM Sample XSLs provided To convert RDF to NTriple To convert RDF to INSERT statements

44 Model: DML SQL DML commands may be used to do DML operations on a base table to effect DML (i.e., triple insert, delete, and update) on the corresponding model Insert Triples INSERT INTO family_table VALUES (1, SDO_RDF_TRIPLE_S( family', '< '< <

45 Model: Security The creator of the base table corresponding to a model can grant privileges to other users To perform DML to a model, a user must have DML privileges for the corresponding base table The creator of a model can grant QUERY privileges on the corresponding database view to other users A user can query only those models for which s/he has QUERY privileges to the corr. database views Only the creator of a model can drop the model

46 Model: Views Database views corresponding to the models

47 RDF Rulebases

48 Rulebase: DDL Procedures provided as part of the API may be used to Create a rulebase create_rulebase('family_rb'); Drop a rulebase drop_rulebase('family_rb'); When a user creates a rulebase, a database view gets created automatically rdfr_family_rb (rule_name, antecedent, filter, consequent, aliases)

49 Rulebase: DML SQL DML commands may be used on the database view corresponding to a target rulebase to insert, delete, and update rules insert into mdsys.rdfr_family_rb values( uncle_rule', (?x :brotherof?y) (?y :parentof?z), NULL, '(?x :uncleof?z)', SDO_RDF_Aliases( ));

50 Rulebase: Security Creator of a rulebase can grant privileges to the corresponding database view to other users Performing DML operations requires invoker to have appropriate privileges on the database view Only the creator of a rulebase can drop the rulebase

51 Rulebase: Views RDF_RULEBASE_INFO Contains the list of rulebases For each rulebase, contains additional information (such as, creator, view name, etc) Content of each rulebase is available from the corresponding database view

52 RDF Rule Indexes

53 Rule Index: DDL Procedures provided as part of the API may be used to Create a rule index create_rules_index ('family_rb_rix_family, SDO_RDF_Models('family'), SDO_RDF_Rulebases( rdfs','family_rb')); Drop a rule index drop_rules_index ('family_rb_rix_family'); When a user creates a rule index, a database view gets created automatically rdfi_family_rb_rix_family ( )

54 Rule Index: Security To create a rule index on an RDF dataset (models and rulebases), user needs to have QUERY privileges on those models and rulebases Creator of a rule index holds QUERY privilege on the rule index and may grant this privilege to other users Only the creator of a rule index can drop it

55 Rule Index: Views RDF_RULEINDEX_INFO Contains the list of rule indexes For each rule index, contains additional information (such as, creator, status, etc) RDF_RULEINDEX_DATASETS For every rule index, stores the names of its models and rulebases

56 Rule Index: Dependencies Content of a rule index depends upon the content of each element of its dataset Any modification to the models or rulebases in its dataset invalidates the rule index Dropping a model or rulebase will drop dependent rule indexes automatically.

57 Summary RDF Data Model Models (Graphs) RDF Query using SDO_RDF_MATCH Table Function RDF Data Model with (user-defined) Rules Models (Graphs) Rulebases Rule Indexes RDF Query on entailed RDF graphs Management (DDL, DML, Security, ) Models, Rulebases, and Rule Indexes

58 RDF Data Model Demo

59 Demo: Family Schema

60 Demo: Family Schema 2

61 Demo: Family Model Data

62 Demo: Family Model Data (Alt)

63 Demo: Query without Inference select m from TABLE(SDO_RDF_MATCH( '(?m rdf:type :Male)', SDO_RDF_Models('family'), null, SDO_RDF_Aliases( SDO_RDF_Alias('', ' null)); M

64 Demo: Query w/ RDFS Inference select m from TABLE(SDO_RDF_MATCH( '(?m rdf:type :Male)', SDO_RDF_Models('family'), SDO_RDF_Rulebases( RDFS ), SDO_RDF_Aliases( SDO_RDF_Alias('', ' null)); M

65 Demo: Family Rulebase Antecedent: (?x :parentof?y) (?y :parentof?z) Filter: NULL Consequent: (?x :grandparentof?z)

66 Demo: Query w/ Family and RDFS Inference select x, y from TABLE(SDO_RDF_MATCH( X '(?x :grandparentof?y) (?x rdf:type :Male)', SDO_RDF_Models('family'), SDO_RDF_Rulebases('RDFS','family_rb'), SDO_RDF_Aliases( SDO_RDF_Alias('',' null)); Y

67 Q U E S T I O N S A N S W E R S

68 Demo of Siderean s Seamark Navigation Server Mike DiLascio & Joanne Luciano

69 Agenda About Siderean Software & Predictive Medicine, Inc. Introducing Seamark Navigation Server v.3.6 Seamark & Oracle 10g RDF Data Model Demonstration of Seamark / Oracle 10g integration Lessons Learned / Q&A

70 About Siderean Software Aggregate, organize and navigate information -the way users think -to improve analysis and decision making. Founded in 2001 and based in El Segundo, CA Ventured backed in 2004 Delivering RDF-centric navigation and analysis capabilities for end users (a.k.a. - the last mile ) Active W3C member leveraging Semantic Web standards Demonstrating integrated Seamark navigation layer over Oracle 10g RDF Data Model in collaboration with Predictive Medicine, Inc.

71 Current solutions 50,000 results!!! Now what? I give up! Hello? Get me an apple! Why do I get oranges when I m looking for apples? IT: As soon as I fix his, hers stops working. CONTENT PRODUCER: I just produced three apples last week! Enterprise search a brute force approach Knowledge management breathtakingly expensive

72 Introducing Seamark Navigation Server I can see the big picture! No more staring at a blank text box. I can drill down quickly to what I want. IT: I can take my coffee break now. CONTENT PRODUCER: I knew we had an apple in here somewhere. Seamark layering organization to deliver pinpoint navigation

73 How it works: process Term Text Person Place View View Event Metadata about data and content is aggregated Organized into a unified information architecture Analyzed to generate on-demand views Providing pinpoint navigation across the data and content

74 How it works: architecture User Navigation and User Tagging Unstructured Content and Data Feeds Web Browsers & Portals Search Engines User Alerts Metadata Aggregator Navigation Metadata Navigation Web Services Feed Aggregators Structured Content Sources

75 Seamark/Oracle integration architecture: Phase 1 User Navigation and User Tagging Web Browsers & Portals User Alerts Oracle 10g RDF Data Model for scalable persistence of metadata Batch RDFMatch Query issued from Seamark at index time Cached Navigation Metadata Navigation Web Services Feed Aggregators

76 Seamark/Oracle integration architecture: Phase 2 User Navigation and User Tagging Web Browsers & Portals User Alerts Oracle 10g RDF Data Model for scalable persistence of metadata Federated RDFMatch Queries issued from Seamark at query time Dynamic Navigation Metadata Navigation Web Services Feed Aggregators

77 Seamark Demo: Background & Concepts Life Sciences demonstration premise RDF offers high value during early stage research Leveraging strengths of Oracle 10g & Seamark v3.6 Oracle large datasets / scalability Seamark useful subsets / flexible navigation & insights Project elapsed time - about one week Locating and identifying data sources represented the greatest time element Data sources in RDF required minimal integration time Non-RDF data sources required transformation and linking values (non-trivial but straightforward)

78 Seamark Demonstration: Identification of new drug candidates Keywords.rdf GO2UniProt.rdf IntAct.rdf UniProt.rdf Citation PubMed.xml GO2Keyword.rdf ProbeSet.rdf Keyword GO2OMIM.rdf Probe Protein Gene MIM Id OMIM.rdf GO.rdf GO2Enzyme.rdf Enzyme Organism Compound Taxonomy.rdf Enzymes.rdf KEGG.rdf Pathway 1. Differentiate different forms of disease 2. Identify patients subgroups. 3. Identify top biomarkers 4. Identify function 5. Identify biological and chemical properties and disease associations of biomarker 6. Identify documents 7. Identify role in metabolic pathways 8. Identify compounds that interact 9. Identify and compare function in other organisms 10. Identify any prior art

79 Live Seamark Life Sciences Demonstration: Sample Screenshots

80 Seamark application start page shows integration of OMIM, GO, KEGG, UniProt and NCBI

81 Select: Probe Set ID: M18255_cds2_s_at

82 Results: 9 Matches on M18255_cds2_s_at to the Gene Ontology Cytoplasm 1 st of 9 Matches Cellular Location Via Gene Ontology

83 Cytoplasm 1 st of 9 Matches Page Scroll

84 Cytoplasm 1 st of 9 Matches Page Scroll Plasma Membrane,, 2 nd of 9 Matches Cellular Location Via Gene Ontology Page Scroll for more results, etc.

85 Start Page: Optionally search across entire collection based upon keywords from the integrated data sources

86 Seamark Lessons Learned RDF offers multiple unconstrained views of data/relationships Provides maximum flexibility during early stage research Later stages can leverage OWL to constrain known relationships Data providers Timing is right to publish in RDF format Cut your customer s integration costs Speed discovery time Even with one week of effort Proof of Concept demonstrates value of broad & deep integration Additional value in extending POC in customer pilot initiatives

87 Siderean Seamark Conclusion Getting the precise information we need from today s data glut is profoundly difficult Solving this problem requires a solution that works the way you think Siderean is the world s first turnkey navigation server for the enterprise and people at large

88 Thank You! To arrange a demonstration of Seamark or for more information please contact: Mike DiLascio Office: Mobile: mdilascio@siderean.com Siderean Software, Inc. 390 North Sepulveda Blvd., Suite 2070 El Segundo, CA USA

89