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INDUS: A System for Information Integration and Knowledge Acquisition from Autonomous, Distributed and Semantically Heterogeneous Data Sources   Jie Bao, Doina Caragea, Jyotishman Pathak, Adrian Silvescu, Carson Andorf, Changhui Yan, Drena Dobbs and Vasant Honavar June 28, 2005
Background and Motivation ,[object Object],[object Object],[object Object],InterPro MIPS Swissprot
Outline ,[object Object],[object Object],[object Object]
Ontology-based information integration in INDUS
Semantically Heterogeneous Data Sources D 1 D 2 Aspartyl/asparaginyl beta-hydroxylase Beta-adrenergic receptor kinase 2 Protein Name 1.14.11.16  Peptide-aspartate  beta-dioxygenase TPR TPR_REGION TPR MAQRKNAKSS GNSSSSGSGS … Q12797 2.7.1.126 Beta-adrenergic receptor kinase RGS PROT_KIN_DOM PH_DOMAIN MADLEAVLAD VSYLMAMEKS … P35626 EC Number Prosite Motifs Protein Sequence Protein ID RIIa HSP70 Pfam Domains 415 692 Length BCY1 SSE1 Gene 16.19.01 cyclic nucleotide binding (cAMP, cGMP, etc.)  VSSLPKESQA ELQLFQNEIN … P07278 16.01 protein binding STPFGLDLGN NNSVLAVARN … P32589 MIPS Funcat AA Sequence Accession Number AN
Capabilities of INDUS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
INDUS Tools ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
INDUS Users: Domain Ontologists ,[object Object],[object Object],[object Object],[object Object],[object Object]
INDUS Users: Data Providers ,[object Object],[object Object],[object Object],[object Object],[object Object]
INDUS Users: Domain Experts ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
INDUS Users: Domain Scientists ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object]
Semantically Heterogeneous Data Data sources need to be made self-describing by specifying the relevant meta data D 1 D 2 Aspartyl/asparaginyl beta-hydroxylase Beta-adrenergic receptor kinase 2 Protein Name 1.14.11.16  Peptide-aspartate  beta-dioxygenase TPR TPR_REGION TPR MAQRKNAKSS GNSSSSGSGS … Q12797 2.7.1.126 Beta-adrenergic receptor kinase RGS PROT_KIN_DOM PH_DOMAIN MADLEAVLAD VSYLMAMEKS … P35626 EC Number Prosite Motifs Protein Sequence Protein ID RIIa HSP70 Pfam Domains 415 692 Length BCY1 SSE1 Gene 16.19.01 cyclic nucleotide binding (cAMP, cGMP, etc.)  VSSLPKESQA ELQLFQNEIN … P07278 16.01 protein binding STPFGLDLGN NNSVLAVARN … P32589 MIPS Funcat AA Sequence Accession Number AN
Meta Data ,[object Object],[object Object],[object Object],[object Object],Schema for protein data in D 1 EC Number: EC Hierarchy Prosite Motifs: Motifs Protein Sequence: AA String Protein Name: String Protein ID : Swissprot ID
Attribute value hierarchy An  attribute value hierarchy  (AVH) is a partial order   ontology over the values of  attributes of data Example: MIPS Funcat Hierarchy
Making data sources self-describing - Ontology-extended data source Data Schema Ontology + + MIPS Funcat:  MIPS Hierarchy Prosite Motifs: Motifs Length:  Positive Integer Gene:  Gene ID Accession Number: MIPS ID RIIa HSP70 415 692 BCY1 SSE1 16.19.01 cyclic nucleotide binding (cAMP, cGMP.)  VSSLPKESQA ELQLFQNEIN P07278 16.01 protein binding STPFGLDLGN NNSVLAVARN P32589
INDUS: Ontology Editor
INDUS: Schema Editor
INDUS: Data Editor
User view MIPS Swissprot User Schema Data Sources of Interest User View User Ontology A  user view   is given by : ,[object Object],[object Object],[object Object],GO Function: GO Hierarchy Structural Class: SCOP  Protein:  AA String Source:  Species String PID: Swissprot ID
Mappings ,[object Object],[object Object],[object Object],[object Object]
Mappings at schema level Protein ID:  Swissprot ID Protein Name:  String Protein Sequence:  AA String Prosite Motifs:  AA String EC Number:  EC Hierarchy Accession No AN:  MIPS ID Gene:  Gene ID AA Sequence:  AA String Length:  Pos Integer MIPS Funcat:  MIPS Hierarchy Pfam Motifs:  Motifs D 1 D 2 PID:  Swissprot ID Protein:  AA String GO Function: GO Hierarchy D U Source:  Species String
Mappings at schema level Protein ID : D 1 ≡  PID : D U Accession Number AN : D 2 ≡  PID : D U Protein ID:  Swissprot ID Protein Name:  String Protein Sequence:  AA String Prosite Motifs:  AA String EC Number:  EC Hierarchy Accession No AN:  MIPS ID Gene:  Gene Set AA Sequence:  AA String Length:  Pos Integer MIPS Funcat:  MIPS Hierarchy Pfam Motifs:  Motifs D 1 D 2 PID:  Swissprot ID Protein:  AA String GO Function: GO Hierarchy D U Source:  Species String
Mappings at schema level Protein ID : D 1 ≡  PID : D U Accession Number AN : D 2 ≡  PID : D U Protein Sequence : D 1 ≡  AA Composition : D U AA Sequence : D 2  ≡  AA Composition : D U Protein ID:  Swissprot ID Protein Name:  String Protein Sequence:  AA String Prosite Motifs:  AA String EC Number:  EC Hierarchy Accession No AN:  MIPS ID Gene:  Gene ID AA Sequence:  AA String Length:  Pos Integer MIPS Funcat:  MIPS Hierarchy Pfam Motifs:  Motifs D 1 D 2 PID:  Swissprot ID Protein: AA String GO Function: GO Hierarchy D U Source:  Species String
Mappings at schema level Protein ID : D 1 ≡  PID : D U Accession Number AN : D 2 ≡  PID : D U Protein Sequence : D 1 ≡  AA Composition : D U AA Sequence : D 2  ≡  AA Composition : D U EC Number : D 1  ≡  GO Function : D U’ MIPS Funcat : D 2  ≡  GO Function : D U Protein ID:  SwissProt ID Protein Name:  String Protein Sequence:  AA String Prosite Motifs:  AA String EC Number:  EC Hierarchy Accession No AN:  MIPS ID Gene:  Gene ID AA Sequence:  AA String Length:  Pos Integer MIPS Funcat:  MIPS Hierarchy Pfam Motifs:  Motifs D 1 D 2 PID:  SwissProt ID Protein:  AA String GO Function: GO Hierarchy D U Source:  Species String
Mappings at ontology level D U D U D 1
Mappings at ontology level EC 2.7.1.126 : D 1   ≡  GO 0047696 : D U D U D 1
Mappings at ontology level D U EC 2.7.1 :  D 1      GO 00047696 :  D U D 1
Mappings at ontology level D 1 EC 2.7.1.126 : D 1      GO 0004672  : D U D U
INDUS: View Editor
INDUS: Mapping Editor
Sample Query ,[object Object],[object Object]
Query processing in Indus Query  Formulation
INDUS: Query Editor
INDUS ,[object Object],[object Object],[object Object],[object Object],[object Object]
Related work ,[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object]
Summary
Work in progress ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Work in progress ,[object Object],[object Object],[object Object],[object Object]
Work in progress ,[object Object],[object Object],[object Object],[object Object]
Work in progress ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Relevant Publications ,[object Object],[object Object],[object Object]
http://www.cs.iastate.edu/~dcaragea/indus.html

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INDUS: A System for Information Integration and Knowledge Acquisition from Autonomous, Distributed and Semantically Heterogeneous Data Sources

  • 1. INDUS: A System for Information Integration and Knowledge Acquisition from Autonomous, Distributed and Semantically Heterogeneous Data Sources Jie Bao, Doina Caragea, Jyotishman Pathak, Adrian Silvescu, Carson Andorf, Changhui Yan, Drena Dobbs and Vasant Honavar June 28, 2005
  • 2.
  • 3.
  • 5. Semantically Heterogeneous Data Sources D 1 D 2 Aspartyl/asparaginyl beta-hydroxylase Beta-adrenergic receptor kinase 2 Protein Name 1.14.11.16 Peptide-aspartate beta-dioxygenase TPR TPR_REGION TPR MAQRKNAKSS GNSSSSGSGS … Q12797 2.7.1.126 Beta-adrenergic receptor kinase RGS PROT_KIN_DOM PH_DOMAIN MADLEAVLAD VSYLMAMEKS … P35626 EC Number Prosite Motifs Protein Sequence Protein ID RIIa HSP70 Pfam Domains 415 692 Length BCY1 SSE1 Gene 16.19.01 cyclic nucleotide binding (cAMP, cGMP, etc.) VSSLPKESQA ELQLFQNEIN … P07278 16.01 protein binding STPFGLDLGN NNSVLAVARN … P32589 MIPS Funcat AA Sequence Accession Number AN
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13. Semantically Heterogeneous Data Data sources need to be made self-describing by specifying the relevant meta data D 1 D 2 Aspartyl/asparaginyl beta-hydroxylase Beta-adrenergic receptor kinase 2 Protein Name 1.14.11.16 Peptide-aspartate beta-dioxygenase TPR TPR_REGION TPR MAQRKNAKSS GNSSSSGSGS … Q12797 2.7.1.126 Beta-adrenergic receptor kinase RGS PROT_KIN_DOM PH_DOMAIN MADLEAVLAD VSYLMAMEKS … P35626 EC Number Prosite Motifs Protein Sequence Protein ID RIIa HSP70 Pfam Domains 415 692 Length BCY1 SSE1 Gene 16.19.01 cyclic nucleotide binding (cAMP, cGMP, etc.) VSSLPKESQA ELQLFQNEIN … P07278 16.01 protein binding STPFGLDLGN NNSVLAVARN … P32589 MIPS Funcat AA Sequence Accession Number AN
  • 14.
  • 15. Attribute value hierarchy An attribute value hierarchy (AVH) is a partial order ontology over the values of attributes of data Example: MIPS Funcat Hierarchy
  • 16. Making data sources self-describing - Ontology-extended data source Data Schema Ontology + + MIPS Funcat: MIPS Hierarchy Prosite Motifs: Motifs Length: Positive Integer Gene: Gene ID Accession Number: MIPS ID RIIa HSP70 415 692 BCY1 SSE1 16.19.01 cyclic nucleotide binding (cAMP, cGMP.) VSSLPKESQA ELQLFQNEIN P07278 16.01 protein binding STPFGLDLGN NNSVLAVARN P32589
  • 20.
  • 21.
  • 22. Mappings at schema level Protein ID: Swissprot ID Protein Name: String Protein Sequence: AA String Prosite Motifs: AA String EC Number: EC Hierarchy Accession No AN: MIPS ID Gene: Gene ID AA Sequence: AA String Length: Pos Integer MIPS Funcat: MIPS Hierarchy Pfam Motifs: Motifs D 1 D 2 PID: Swissprot ID Protein: AA String GO Function: GO Hierarchy D U Source: Species String
  • 23. Mappings at schema level Protein ID : D 1 ≡ PID : D U Accession Number AN : D 2 ≡ PID : D U Protein ID: Swissprot ID Protein Name: String Protein Sequence: AA String Prosite Motifs: AA String EC Number: EC Hierarchy Accession No AN: MIPS ID Gene: Gene Set AA Sequence: AA String Length: Pos Integer MIPS Funcat: MIPS Hierarchy Pfam Motifs: Motifs D 1 D 2 PID: Swissprot ID Protein: AA String GO Function: GO Hierarchy D U Source: Species String
  • 24. Mappings at schema level Protein ID : D 1 ≡ PID : D U Accession Number AN : D 2 ≡ PID : D U Protein Sequence : D 1 ≡ AA Composition : D U AA Sequence : D 2 ≡ AA Composition : D U Protein ID: Swissprot ID Protein Name: String Protein Sequence: AA String Prosite Motifs: AA String EC Number: EC Hierarchy Accession No AN: MIPS ID Gene: Gene ID AA Sequence: AA String Length: Pos Integer MIPS Funcat: MIPS Hierarchy Pfam Motifs: Motifs D 1 D 2 PID: Swissprot ID Protein: AA String GO Function: GO Hierarchy D U Source: Species String
  • 25. Mappings at schema level Protein ID : D 1 ≡ PID : D U Accession Number AN : D 2 ≡ PID : D U Protein Sequence : D 1 ≡ AA Composition : D U AA Sequence : D 2 ≡ AA Composition : D U EC Number : D 1 ≡ GO Function : D U’ MIPS Funcat : D 2 ≡ GO Function : D U Protein ID: SwissProt ID Protein Name: String Protein Sequence: AA String Prosite Motifs: AA String EC Number: EC Hierarchy Accession No AN: MIPS ID Gene: Gene ID AA Sequence: AA String Length: Pos Integer MIPS Funcat: MIPS Hierarchy Pfam Motifs: Motifs D 1 D 2 PID: SwissProt ID Protein: AA String GO Function: GO Hierarchy D U Source: Species String
  • 26. Mappings at ontology level D U D U D 1
  • 27. Mappings at ontology level EC 2.7.1.126 : D 1 ≡ GO 0047696 : D U D U D 1
  • 28. Mappings at ontology level D U EC 2.7.1 : D 1  GO 00047696 : D U D 1
  • 29. Mappings at ontology level D 1 EC 2.7.1.126 : D 1  GO 0004672 : D U D U
  • 32.
  • 33. Query processing in Indus Query Formulation
  • 35.
  • 36.
  • 37.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.

Hinweis der Redaktion

  1. INDUS – a federated, query centric approach to the problem of knowledge acquisition from distributed, semantically heterogeneous, autonomous data sources Learning algorithms that can be decomposed into information gathering (obtained by answering queries) and hypothesis generation can be easily linked to INDUS INDUS makes possible the exchange of data and findings between scientists or institutions working on related problems (e.g., bioinformatics)
  2. Design that is tailored for predictive model building using machine learning algorithms from distributed, semantically heterogeneous, autonomous data sources
  3. INDUS – a federated, query centric approach to the problem of knowledge acquisition from distributed, semantically heterogeneous, autonomous data sources Learning algorithms that can be decomposed into information gathering (obtained by answering queries) and hypothesis generation can be easily linked to INDUS INDUS makes possible the exchange of data and findings between scientists or institutions working on related problems (e.g., bioinformatics)