MAFRA – A MApping FRAmework for Distributed Ontologies

1. MAFRA – A MApping FRAmework for Distributed Ontologies Alexander Maedche, Boris Motik, Nuno Silva and Raphael Volz FZI, University of Karlsruhe Presented by Francisco Martin-Recuerda Digital Enterprise Research Institute (DERI)

2. Outline • MAFRA • Conceptual Framework • Semantic Bridging • Example WP4 - Ontology Mediation

3. MAFRA Framework for mapping distributed ontologies implemented within KAON (Ontology Management tool developed by University of Karlsruhe): • Horizontal dimension: defines the phases in a mapping process (Lift &Normalization, Similarity, Semantic Bridging, Execution and Postprocesing). • Vertical dimension: defines the modules that interact with the elements of the horizontal dimension (Evolution, Domain Knowledge & Constraints, Cooperative Consensus building and GUI). WP4 - Ontology Mediation

4. MAFRA WP4 - Ontology Mediation

5. Conceptual Framework – Horizontal Dimension • Lift & Normalization Define a uniform representation (in RDF(S)) in order to normalized the ontologies that we want to map. In the proccess syntax differences are eliminated and the semantic diferences are slighly reduced. The result is a list of normalized lexica. • Similarity Multi-strategy proccess that calculated similarities between ontology entities using different algorithms. • Semantic Bridging Relate semantically entities from the source and target ontologies encapsulating all necessary information to transform instances of one source ontology entity to instances of one target ontoogy entity . WP4 - Ontology Mediation

6. Conceptual Framework – Horizontal Dimension (II) • Execution This module actually transforms instances from the source ontology into target ontology by evaluating the semantic bridges defined earlier • Post-processing Take the results of the execution module to check and improve the quality of the transformation results (like object identity: recognize that two instances represent the same real-world object). WP4 - Ontology Mediation

7. Horizontal Dimension - Similarity • Lexical similarity Using Wordnet and altered Resnik algorithm, the strategy focuses on map terms with lexical similarities. • Property similarity Map concepts with similar properties (attributes and/or relations) • Bottom-up similarity The algorithm tries to discover new similarities analizing mapping elements of the taxonomy from the lower level to upper level . • Top-down similarity It is like the previous one, but it starts from the upper level to the lower level WP4 - Ontology Mediation

8. Horizontal Dimension – Semantic Bridging (Steps) • Stablish a mapping of entities to be bridge. (based in the similarities founded in the previous phase). • Specify matching properties for each concept bridge. • Look for no target concepts. (It is not possible to find a target for a source concept, the algorithm looks for if there are source superconcept mappings and map the source concept in the same way). • Improve quality of bridges between source sub-/concepts and target concepts. • Associate transformation procedures to translations. (define how translates source instances into target instances) . WP4 - Ontology Mediation

9. Horizontal Dimension – Semantic Bridging (Nature) • Entity dimension SBs may relate ontology entities (concepts, relations, attributes and extensional patterns (modeling the content of the instance)). • Cardinality dimension Determine the number of ontology entities at both sides of the semantic bridge. • Structural dimension Define how semantic bridges may be combined into more complex bridges. • Constraint dimension Define conditions that must hold the execution module when transforms instances from the source ontology into the target ontology. • Transformation dimension Reflect how instances of the source ontology are transformed during the mapping process. WP4 - Ontology Mediation

10. Horizontal Dimension – Semantic Bridging Ontology (SBO) • Semantic Bridging Ontology (SBO) Specification (using DAML+OIL) of all available semantic bridges organized in a taxonomy. • Classes Concepts, Relations and Attributes Represent the entities of the mapping ontologies. • Class Semantic Bridge Define the relations to source and target entities. • Class Service Reference resources that are responsible to connect to or describe transformations. • Class Rule Represent constraint and transformation-relevant information. WP4 - Ontology Mediation

11. Horizontal Dimension – Semantic Bridging Ontology (SBO) (II) • Class Transformation Associate with a transformation procedure a set of extra requirements. • Class Condition Represent the conditions that should be verified in order to execute a semantic bridge • Class Composition Allow to any semantic bridge to aggregate many different bridges. • Class Alternative Group several mutual exclusive semantic bridges. WP4 - Ontology Mediation

12. Horizontal Dimension – Semantic Bridging Ontology (SBO) (III) WP4 - Ontology Mediation

13. Conceptual Framework – Vertical Dimension • Evolution Syncrony the changes in the source and target ontologies with the semantic bridges defined by the Semantic Bridge module. • Cooperative Consensus Building From multiple alternative possible mappings the tool help to stablish a consensus between several proposals of people involved in the mapping task. • Domain constraints and Background Knowledge. The tool allow users to include estra-information (glossaries to help indentify synoms, lexical ontologies like Wordnet) to improve the improve the quality of the mapping. • GUI Make the work to visualize the elements of the source and target ontologies much easier in the same way that the semantic bridges stablished to represent the mapping between entities. WP4 - Ontology Mediation

14. Example WP4 - Ontology Mediation

15. Example WP4 - Ontology Mediation