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Ontology-Based Data Mediation for Semantic Environments

Ontology-Based Data Mediation for Semantic Environments. PhD Thesis Defense Candidate: Adrian Mocan Supervisor: Prof. Dr. Manfred Hauswirth National University of Ireland, Galway, Ireland 3 rd of July, 2008. Overview. Context and Motivation Formal Model for Mappings Creation

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Ontology-Based Data Mediation for Semantic Environments

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  1. Ontology-Based Data Mediation for Semantic Environments PhD Thesis Defense Candidate: Adrian Mocan Supervisor: Prof. Dr. Manfred Hauswirth National University of Ireland, Galway, Ireland 3rd of July, 2008

  2. Overview • Context and Motivation • Formal Model for Mappings Creation • Design-time Ontology Mapping • Run-time Data Mediation • Evaluation • Conclusions National University of Ireland, Galway

  3. Motivation and Context • Semantic Web Services • Semantic Execution Environment • Enable the discovery, selection, composition, invocation of Web Services • Different ontologies might be used in describing services offered by different providers • Mediation required during the discovery, invocation • Data mediation solutions are required National University of Ireland, Galway

  4. Problem Definition • Instance Transformation scenario National University of Ireland, Galway

  5. Formal Model Solution • Design-time / Run-time Separation • Software implementations have been developed National University of Ireland, Galway

  6. Formal Model Main Contributions • Formal Model for the mapping creation • Ontology language independent model • Formalizing the main concepts behind both the design-time and run-time phases • Algorithms and methods are expressed in terms of this model • Can be applied to approaches targeting other ontology models/languages • Inherited by the grounding of the model to the same ontology model National University of Ireland, Galway

  7. Items Primitive Items Compound Items Description Items Relationships describes Description Item Compound Item successor Description Item Successor Item Primitive Item Compound Item is a is a Successor Item Description Item successor describes Successor Items Abstract Elements • Entities described by other entities Primitive Item Compound Item x.(ci(x) <=> y.(di(y) ٨ describes(y, x))) (1) x.y.(describes(x, y) => ci(y) ٨ di(x)) (2) x.(di(x) <=> y.(si(y) ٨successor(y, x))) (3) x.y.(successor(x, y) => di(y) ٨ si(x)) (4) x.(si(x) => pi(x) ∨ ci(x))) (5) x.((ci(x) ٨ pi(x))) (6) x.((ci(x) ٨ di(x))) (7) x.((pi(x) ٨ di(x))) (8) National University of Ireland, Galway

  8. Perspectives and Contexts [1] • Perspectives • Contexts National University of Ireland, Galway

  9. PI_1 PI_2 CI_1 describes CI_2 DI_11 CI_3 successor Context n PI_1 DI_31 successor CI_2 describes PI_2 DI_21 successor describes describes CI_3 DI_22 successor Perspectives and Contexts [2] Perspective = Context 0 National University of Ireland, Galway

  10. Mapping Operation • Mapping Context: • Operation: • Contexts update • Creation of mappings • Depends on the chosen x and y • Depends on the perspectives • Depends on the current contexts National University of Ireland, Galway

  11. PI_1 PI_2 CI_1 Context 2 Context 1 describes Decomposition CI_2 DI_11 CI_3 CI_3 successor PI_1 PI_1 DI_31 DI_31 successor successor CI_2 CI_2 CI_2 Decomposition Decomposition describes describes describes PI_2 PI_2 PI_2 DI_21 DI_21 DI_21 successor successor successor describes describes describes describes describes CI_3 CI_3 CI_3 DI_22 DI_22 DI_22 successor successor successor Decomposition and Contexts Context 0 Context 1 National University of Ireland, Galway

  12. Design-time Ontology Mapping • First phase of the mediation solution • Human-driven activity • Produces a set of mappings (i.e. an alignment between two ontologies) National University of Ireland, Galway

  13. Design-time Ontology MappingMainContributions • Design-time Ontology Mapping • Based on the Formal Model • New techniques able to enhance the semi-automatic aspect of ontology mapping • Ontology perspectives • Decomposition and Mapping Contexts • Top-down and Bottom-up mapping strategies • Implementation of these techniques as part of a mapping tool National University of Ireland, Galway

  14. Ontology Perspectives [1] • Semi-automatic methods involve graphical tools and techniques for ontology visualization • Depending of the visualization technique on the ontology certain mismatches become easier/harder to address • The perspectives or the view-points adopted to visualize the source and the target ontologies play a crucial role National University of Ireland, Galway

  15. Ontology Perspectives [2] • Each ontology perspective involves one instantiation of the model National University of Ireland, Galway

  16. Ontology Perspectives [3] Source Ontology Target Ontology National University of Ireland, Galway

  17. Ontology Perspectives [3] Target Ontology Source Ontology • string • integer • date • human • name→string • age→integer • noOfChildren→integer • man • name→string • age→integer • noOfChildren→integer • woman • name→string • age→integer • noOfChildren→integer • marriage • hasParticipant→human • date→date • string • integer • person • name→string • age→integer • hasGender→gender • hasChild→person • marriedTo→person • gender • value→string PartOf pi data types, concepts without attributes ci concepts with attributes di attributes PartOf National University of Ireland, Galway

  18. Ontology Perspectives [3] Source Ontology Target Ontology • string • integer • person • hasGender→male:gender • hasGender→female:gender • gender • string • integer • human • man • woman • marriage InstanceOf InstanceOf di attributes that can be filled by constants (afc) included in the ontology ci concepts with at least one afc pi data types, concepts without any afc-s National University of Ireland, Galway

  19. Ontology Perspectives [3] Target Ontology Source Ontology • string • integer • date • human • name→string • age→integer • noOfChildren→integer • man • name→string • age→integer • noOfChildren→integer • woman • name→string • age→integer • noOfChildren→integer • marriage • hasParticipant→human • date→date • string • integer • date • person • gender • name • hasDomain→person • hasRange→string • age • hasDomain→person • hasRange→integer • ... • marriedTo • hasDomain→person • hasRange→person • value • hasDomain→gender • hasRange→string PartOf pi concepts ci attributes di {hasDomain, hasRange} RelatedBy National University of Ireland, Galway

  20. Implementing Perspectives • Each role (i.e. items) have to be filled by an ontological entity • Each relationship has to be defined (i.e. describes, successor) • Define what kind mappings can be created using combination of these perspectives • Three perspectives defined in this thesis • PartOf, InstanceOf, RelatedBy • Two of them fully implemented in the mapping tool National University of Ireland, Galway

  21. Decomposition and Context [1] • Not all the information contained in the perspective is needed in a given step • By isolating the domain experts from the unnecessary information they can better concentrate on their tasks National University of Ireland, Galway

  22. Decomposition and Context [2] National University of Ireland, Galway

  23. Top-Down and Bottom-Up Mapping Strategies • Bottom-Up • Start from the simple entities to be mapped • Continue with more complex ones • Top-Down • Start from what is of interest to be mapped in the two ontologies • The semi-automatic support guides the next steps • Employ two aspects of the semi-automatic support • Suggestion Algorithms • Decomposition and context • These two strategies can be combined National University of Ireland, Galway

  24. Concept2Concept (C2C) Attribute2Attribute (A2A) Concept2Attribute (C2A) Attribute2Concept (A2C) Schema elements (e.g. concepts, attributes) Restriction on the schema elements (e.g. allowed values for an attribute) Ontology Mappings • Abstract representation of mappings • Alignment format developed as part of the KW [ESS06] mapping(sourceEntity; [sourceEntityRestriction]; targetEntity; [targetEntityRestriction]; typeOfMapping) [ESS06] J. Euzenat, F. Scharffe, and L. Serafini. Specification of the alignment format. Knowledge Web Deliverable D2.2.6, 2006. National University of Ireland, Galway

  25. Design-time Ontology MappingSummary • Allows the semi-automatic creation of mappings between a Source and a Target Ontology • Goals • Graphical interface • Set of mechanisms towards semi-automatic creation of mappings • Capturing the semantic relationships identified in the process • Storing these mappings in a persistent storage • Output • Abstract representation of the mappings National University of Ireland, Galway

  26. Run-time Data Mediation • Second phase of the mediation solution • Once the mappings are available they can be used to do data mediation • Mappings need to be “prepared” for a mediation scenario and executed National University of Ireland, Galway

  27. Run-time Data MediationMain Contributions • Main Contributions • Engine implemented on top of a generic rule-reasoner • Decoupling between abstract representation of mappings and their executable representation • Grounding of the abstract representation1 to F-Logic • Dynamic generation of rules based on the heterogeneous data to be mediated 1The abstract representation of mappings is not part of the work in this thesis National University of Ireland, Galway

  28. Run-time Phase [1] • Grounding the abstract mappings • Associate a formal semantics to the mappings • Obtain rules in a concrete language • Why not at design time? • Offers a grater flexibility • Different groundings for the same mappings set • Different execution environments for the grounded mappings • Easier to maintain the abstract mappings • Important point of alignment • Caching mechanism can be used National University of Ireland, Galway

  29. Run-time Phase [2] • Main Mediation Scenario: Instance Transformation • Inputs • Mappings • Incoming data • Source ontology instances • Features • Completely automatic process • Grounding of the abstract mappings to a concrete language • F-Logic, WSML-Rule • Relies on reasoner to evaluate the mapping rules • Outputs • Mediated data • Target ontology instances National University of Ireland, Galway

  30. Evaluation  • Implicit evaluation • Tools have been implemented based on the conceptual ideas • Applied on show-cases in European projects (DIP, SemanticGov, SEEMP, SUPER) National University of Ireland, Galway

  31. EvaluationSEEMP Project  • 3 ontology sets • ARL: 323 Concepts, 296 Axioms • EURES: 425 Concepts, 395 Axioms • Reference Ontology: 485 Concepts, 13 Axioms National University of Ireland, Galway

  32. Evaluation  • Implicit evaluation • Tools have been implemented based on the conceptual ideas • Applied on show-cases in European projects (DIP, SemanticGov, SEEMP, SUPER) • Explicit evaluation • Ontology Mapping Tool Comparison • MAFRA, PROMPT • Formal Model evaluation • Measures from conceptual and reference modeling National University of Ireland, Galway

  33. Conclusions • Ontology-based Data Mediation Solution • New methods for enhancing the machine support during the mapping process • Focuses on Instance transformation scenario • Provides on ontology language independent formal model • Formal and reusable definition of several strategies and methods for semi-automatic mappings creation • Software implementation of the main conceptual ideas National University of Ireland, Galway

  34. Thank you for your attention! Q&A National University of Ireland, Galway

  35. Back-up Slides National University of Ireland, Galway

  36. Formal Model National University of Ireland, Galway

  37. Quality Analysis of Mappings [1] • The Formal model can be used in assessing the quality of mappings • From the Instance Transformation scenario point of view • Completeness of Mappings • Complete Mappings for the Source Data • Complete Mappings for the Target Data National University of Ireland, Galway

  38. Quality Analysis of Mappings [2] • Containment of Mappings • Maximality of Data Structures National University of Ireland, Galway

  39. Design-time Phase National University of Ireland, Galway

  40. PartOf Perspective • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept National University of Ireland, Galway

  41. PartOf to PartOf Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • classtoclassmapping(classMapping) National University of Ireland, Galway

  42. PartOf to PartOf Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • class to class mapping (classMapping) • attribute to attribute mapping (attributeMapping) National University of Ireland, Galway

  43. PartOf to PartOf Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • class to class mapping (classMapping) • class to class mapping (classMapping) • class to attribute mapping (classAttributeMapping) National University of Ireland, Galway

  44. PartOf to PartOf Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • primitive_concept (data type) • compound_concept • attribute1→primitive_concept • attribute2→compound_concept • class to class mapping (classMapping) • class to class mapping (classMapping) • class to attribute mapping (classAttributeMapping) National University of Ireland, Galway

  45. InstanceOf Perspective • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept National University of Ireland, Galway

  46. InstanceOf to InstanceOf Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept • classtoclassmapping(classMapping) National University of Ireland, Galway

  47. InstanceOf to InstanceOf Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept • class to class mapping (classMapping) • attribute to attribute mapping (attributeMapping) • 2*attributeValueCondition(valueCondition) National University of Ireland, Galway

  48. InstanceOf to InstanceOf Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept • regular_concept • instance_concept • attribute1→regular_concept • attribute2→instance_concept • class to class mapping (classMapping) • class to class mapping (classMapping) • class to attribute mapping (classAttributeMapping) • AttributeTypeCondition National University of Ireland, Galway

  49. RelatedBy Perspective • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • concept • attribute • hasDomain→concept • hasRange→concept • concept • attribute • hasDomain→concept • hasRange→concept National University of Ireland, Galway

  50. RelatedBy to RelatedBy Mappings • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • primitive_item • compound_item • hasDescription1→primitive_item • hasDescription2→compound_item • concept • attribute • hasDomain→concept • hasRange→concept • concept • attribute • hasDomain→concept • hasRange→concept • attribute to attribute mapping(attributeMapping) National University of Ireland, Galway

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