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Coastal Atlas Interoperability - Ontologies (Advanced topics that we did not get to in detail)

Coastal Atlas Interoperability - Ontologies (Advanced topics that we did not get to in detail). Luis Bermudez Stephanie Watson Marine Metadata Interoperability Initiative. 1. Overview. Goals Introduction to Ontologies Ontology Components and Practical Exercise Advanced Ontology Concepts

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Coastal Atlas Interoperability - Ontologies (Advanced topics that we did not get to in detail)

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  1. Coastal Atlas Interoperability - Ontologies(Advanced topics that we did not get to in detail) Luis Bermudez Stephanie Watson Marine Metadata Interoperability Initiative 1

  2. Overview • Goals • Introduction to Ontologies • Ontology Components and Practical Exercise • Advanced Ontology Concepts • Mappings • Restrictions and Description Logic • SPARQL and Rules • MMI Tools • Ontology Engineering • Interoperability Demonstration • Discussions 2

  3. Mapping ala SKOS An RDF vocabulary for describing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies', other types of controlled vocabulary, and also concept schemes embedded in glossaries and terminologies

  4. SKOS • provides a standardized way of representing KOS, such as thesauri, classification schemes, and taxonomies • uses RDF • RDF vocabularies: • SKOS Core (for describing KOS) • SKOS Mapping (for mapping between concepts - broad, narrow, exact match) • SKOS Extensions 4

  5. Mapping ala SKOS • import skos.owl • it defines 3 convenient properties to relate instances

  6. Import the 2 atlas ontologiesthat were created by the 2 groups

  7. Make relations between your aX.owl file and one of the atlas files • select one of your favorite topics in your aX.owl file and create an skos:relation (broad, narrow, exact match) to a topic from one of the atlases. • Need to add the skos:property in the Resource Form

  8. Adding SKOS Property(ies) in Resource Form Drag and drop

  9. Commit to SVN - check the web site to make sure your file is there • Meanwhile, atlas experts - make SKOS type mappings among the terms in your atlases

  10. Categorization by propertiesor the world of restrictionsor defining classes using Description Logics (DL)

  11. Story... Facts: • We are in 2010... • SuperAtlas is a super ontology for atlas features. It was signed in 2009 in Monterey by 103 web atlas representatives. • Each group is now an atlas and will have 4 SuperAtlas Features available in the next 20 minutes.

  12. Steps • We will define categories as allowed in OWL-DL. • The definitions of the categories are based on the SuperAtlas Ontology, which is the common vocabulary. • We will run the inferencer, which will automatically categorize your instances.

  13. SuperAtlas Ontology

  14. Process • Import SuperAtlas Ontology • Create a class “PersonRecreationalFeature” which is a sub (or sub-sub) class of your:PersonConcept • make it subclass of superatlas:RecreationalFeature

  15. Create features (e.g. places that could appear in an atlas)

  16. Add Facts about Those Features: • Relative location • add values to isPartOf • add an existing region • Activities that can occur • add an Activity • create/add new instance

  17. You should have 4 instances similar to these:

  18. Defining Classes using Description Logics

  19. Defining a Class in OWL DL Example: Define EuropeanRegion = All regions that are part of Europe. More formally:

  20. Equivalent Restrictions European Region run inference Classifies UnitedKingdom If it is known that an individual is a European Region, it can be inferred that it isPartOf Europe and it’s also a Region; AND also the converse-- If it is known that an individual isPartOf Europe and it is also a Region, then it can be inferred that it is a European Region

  21. Subclass Restrictions European Town run inference Classifies EuropeanTown If it is known that an individual is a European Town, it can be inferred that isPartOf a European Region and it’s also a Region; However, the converse can not be inferred: if it is known that an individual isPartOf a European Region and it is a Region that it is, in fact, a European Town

  22. Restriction Keywords

  23. Restriction Keywords (cont.)

  24. Complex Expressions Example: Person and hasChild some (Person and (hasChild all Man) and (hasChild some Person)) describes the set of people who have at least one child that has some children that are only men (i.e., grandparents that only have grandsons). Note that brackets should be used to clarify the meaning of the expression.

  25. Restrictions Exercise Create a WebCategory class with these subclasses: - AmericanRegion - SwimmingPlacesInAmerica .....

  26. BREAK 10:30-10:45 78

  27. SPARQL AND RULES 78

  28. SPARQL • Query language for RDF (similar to SQL) • Think - triple triple triple • How many triple matches the pattern: • x rdfs:type y • superAtlas:Swimming x y • superAtlas:Swimming rdf:type x 78

  29. SPARQL Examples PREFIX table: <http://www.daml.org/2003/01/periodictable/PeriodicTable#> SELECT ?name ?symbol ?number ?color FROM <http://www.daml.org/2003/01/periodictable/PeriodicTable.owl> WHERE { ?element table:name ?name. ?element table:symbol ?symbol. ?element table:atomicNumber ?number. OPTIONAL { ?element table:color ?color. } } 79

  30. Examples • Find all the subclasses of superatlas:Feature SELECT ?subject WHERE { ?subject rdfs:subClassOf superatlas:Feature } • Find all the features that have an activity of type Sports SELECT ?feature WHERE { ?feature rdf:type superatlas:Feature. ?feature superatlas:hasActivity ?activity. ?activity rdf:type superatlas:Sports. }

  31. Create your own queries • ...

  32. Using Rules • OWL is limited in expressiveness. • can’t combine properties (e.g., uncle is a composition of brother and parent) • can’t use computed values or arithmetic comparisons (e.g., stating that a teenager is a person with age between 13 and 19) • Semantic Web Rule Language (SWRL) • combines OWL and RuleML • proposed to standardize the expression of rules in OWL • Open ontology and view rules

  33. Rules Rule is simple: If A then B or A -> B Semantic Web Rule Language (SWRL) swrl:body -> swrl:head or using JENA rules - very similar syntax

  34. Rules Exercise • Import jena.owl

  35. Configure Inferencing 1 2 3 5 4 6

  36. Example • Create a rule to infer all american sports • Create a class under WebCategories and add a jena:Rule property (drag it) • e.g. AmericanSports

  37. MMI Tools • VOC2OWL • to convert CVs into a common language, OWL • VINE • to map between CVs/ontologies represented in OWL • SEMOR • matches your search term to terms from other controlled vocabularies to find data and information

  38. Ontology Engineering

  39. Ontology Engineering

  40. Engineering Lifecycle From help system TobBraid Composer tutorial

  41. What we did .... • Controlled Vocabularies • your topics • web portal controlled vocabulary • Mappings • among your topics and the FOAF one • among atlas and upper atlas ontology • Categories • Infer hierarchies • Knowledge of a Domain • Formal definition of classes • Rules expression • MMI Tools • Ontology Engineering All web distributed All machine friendly

  42. Slides acknowledgments • Robert Laurini INSA –Lyon http://lisi.insa-lyon.fr/~laurini • TopBraid tutorial

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