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Creating and Querying an Integrated Ontology for Molecular and Phenotypic Cereals Data

Special Session on Agricultural Metadata & Semantics 2nd International Conference on Metadata & Semantics Research October 10-11, 2007 - Corfu, Greece. Creating and Querying an Integrated Ontology for Molecular and Phenotypic Cereals Data. Sonia Bergamaschi, Antonio Sala

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Creating and Querying an Integrated Ontology for Molecular and Phenotypic Cereals Data

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  1. Special Session on Agricultural Metadata & Semantics 2nd International Conference on Metadata & Semantics Research October 10-11, 2007 - Corfu, Greece Creating and Querying an Integrated Ontology for Molecular and Phenotypic Cereals Data Sonia Bergamaschi, Antonio Sala www.dbgroup.unimo.it DII - Dipartimento di Ingegneria dell’Informazione Università di Modena e Reggio Emilia, via Vignolese 905, 41100 Modena Funded by: FIRB project NeP4B: Networked Peers for Business (www.dbgroup.unimo.it/nep4b) and IST FP6 STREP project STASIS (www.dbgroup.unimo.it/stasis)

  2. Motivations • Numerous public data sources have been realized and are now available for researchers in the field of molecular biology • Problem of having access to this great amount of data: • Numerous sources • Heterogeneous interfaces and structures • Low IT skills of the users • What is needed: • Extracting and fusing information from different data sources • Presenting the information according to a unique interface in a transparent and easy way independently from the format of the different sources

  3. CEREALAB project • Conducted by the Agrarian faculty of the University of Modena and Reggio Emilia funded by the Regional Government of Emilia Romagna • The aim is to perform intelligent data integration of existing databases, i.e. to create a Global Virtual Schema (GVV) for the genotypic selection of cereal cultivars • Genotypic selection of cereal cultivars: • To extract genotypic data correlated to phenotypic traits • 3 species involved: • Wheat • Barley • Rice

  4. The MOMIS System gene FHB Wrapper Wrapper Wrapper Wrapper gene gene gene FHB FHB FHB Wrapper Wrapper Graingenes CEREALAB Gramene GRIN CRA ERData MOMIS (Mediator Environment for Multiple Information Sources) (www.dbgroup.unimo.it/Momis) is a framework to perform information extraction and integration from heterogeneous distributed data sources and query management Global Virtual View (GVV)

  5. Integration Process Overview COMMON THESAURUSGENERATION GVV GENERATION (CEREALAB) WRAPPING SYNSET# SCHEMA DERIVEDRELATIONSHIPS ODLI3LOCAL SCHEMA 1 GLOBAL CLASSES SYNSET4 SYNSET1 SYNSET2 LEXICON DERIVEDRELATIONSHIPS CEREALAB Common Thesaurus Structured source clustersgeneration ODLI3LOCAL SCHEMA 2 OWL Export Graingenes Structured source USER SUPPLIEDRELATIONSHIPS ODLI3 LOCAL SCHEMA 3 MAPPINGTABLES INFERRED RELATIONSHIPS GRIN Structured source AUTOMATIC/ MANUALANNOTATION SEMI-AUTOMATIC ANNOTATION

  6. Data Sources • Molecular data: • Gramene, Relational DB (www.gramene.org) • Graingenes, Relational DB (wheat.pw.usda.gov/GG2) • CEREALAB experimental data, Relational DB • Phenotypic Data: • GRIN, Excel Files (www.ars-grin.gov) • CEREALAB repository, Relational DB (created collecting data from specific literature for regional germplasms and from the italian National Council of Research in Agriculture (CRA)) • All these data sources, if considered separately, present incomplete information for the purpose of the CEREALAB project and are sometimes overlapping

  7. Local Source Schemata Annotation Local Source Annotation • To assign meanings (by WordNet) to each local class and attribute name of a local schema • Semi-automatically performed • a WordNet Editor is available to extend WordNet by adding new domain-dependent terms and synsets • This extension step has to be performed just the first time a domain is handled. Gene: a segment of DNA that is involved in producing a polypeptide chain; it can include regions preceding and following the coding DNA as well as introns between the exons; it is considered a unit of heredity) "genes were formerly called factors" Automatic Annotation (Present in WordNet) Marker: A segment of DNA with an identifiable physical location on a chromosome for any feature that has been genetically mapped Marker: some conspicuous object used to distinguish or mark something "the buoys were markers for the channel" Manual Annotation (Not present in WordNet)

  8. Common Thesaurus Generation • MOMIS constructs a Common Thesaurus including SYN, BT/NT, and RT relationships among schema elements. • The Common Thesaurus is constructed through an incremental process in which the following relationships are added: • schema-derived relationships • lexicon-derived relationship • designer-supplied relationships • inferred relationships • As an example: gene is identified as a BT of allele (as gene is a direct hypernym of allele) marker is identified as a NT of gene (as genetic marker as been added as a direct hyponym of gene)

  9. Global Virtual Schema Generation Mappings are generated among global and local classes in the cluster (according to a GAV approach) A Mapping Table (MT) is automatically generated for each global class of a GVV MOMISidentifies and groups classes that describe the same or semantically related concept in different sources into clusters (global classes) • The designer may interactively refine and complete the proposed integration by adding • Data Conversion Functions from local to global attributes or Resolution Functions for global attributes to solve data conflicts of local attribute values Source, Reference: a publication (or a passage from a publication that is referred to

  10. Join Conditions • Object identification: merging data from different sources requires different instantiations of the same real world object to be identified • Join Conditions among pairs of local classes belonging to the same global class allow to identify instances of the same object and fuse them. (CEREALAB.gene.name) = (gramene.gene.name)

  11. The Global Virtual Schema (GVV) • Each GVV element is automatically annotated w.r.t. WordNet and can be exported in OWL • The GVV can be seen as an Ontology of the underlying sources • This Ontology correlates the molecular data of Gramene, Graingenes and the CEREALAB project with the phenotypic data of the GRIN database and those collected by the CEREALAB project

  12. The Integrated Ontology • Molecular data associated with germplasms and phenotypic evaluations

  13. The Integrated Ontology Phenotypic data are divided into six categories chosen among those of major interest for the cereal breeders: • Abiotic Stress • Biotic Stress • Growth and Development related traits • Quality traits • Yield traits.

  14. The Integrated Ontology • For each trait the specific evaluation of a germplasm for that trait is available

  15. The Integrated Ontology • Molecular data are related to phenotypic data indicating their presence in a germplasm for which a quantitative phenotypic evaluation is available • Information about specific molecular markers that can identify genes or QTLs that express a particular phenotypic trait. • In this way genotypic selection of cereals cultivars can be performed starting from phenotypic data

  16. Querying the Integrated Ontology The MOMIS Query Manager is the coordinated set of functions which takes an incoming query (say global query) and performs the following steps: • Query rewriting • to rewrite a global query as an equivalent set of queries expressed on the local sources (local queries) • Local queries execution • the local queries are sent and executed on local sources • Fusion and Reconciliation • The local answers are fused into the global answer • A Graphical User Interface has been developed to compose queries over the GVV regardless of the specific languages of the source databases.

  17. Example “Find information about wheat QTLs that express resistance to the Fusarium fungus”

  18. Example “Find information about wheat QTLs that express resistance to the Fusarium fungus”

  19. Example “Find information about wheat QTLs that express resistance to the Fusarium fungus”

  20. Example “Find information about wheat QTLs that express resistance to the Fusarium fungus”

  21. Example “Find information about wheat QTLs that express resistance to the Fusarium fungus”

  22. Example “Find information about wheat QTLs that express resistance to the Fusarium fungus”

  23. Example “Find information about wheat QTLs that express resistance to the Fusarium fungus”

  24. Conclusions • The MOMIS system allows a straightforward creation of a Global Virtual Schema to integrate data from the CEREALAB research project with data coming from the databases Gramene, Graingenes and GRIN • The integration process provides a unique interface for the 3 sources according to a common ontology • Querying the 3 sources results completely transparent and easy to the user through a GUI • A unique answer is obtained

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