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 –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 ontologies that 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 properties or the world of restrictions or defining classes using Description Logics (DL)

11 Story... Facts: We are in 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:

Equivalent Restrictions European Region Classifies UnitedKingdom run inference 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

Subclass Restrictions European Town 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 run inference

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.....

BREAK 10:30-10:45 78

SPARQL AND RULES 78

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

SPARQL Examples PREFIX table: iodicTable# SELECT ?name ?symbol ?number ?color FROM iodicTable.owl WHERE { ?element table:name ?name. ?element table:symbol ?symbol. ?element table:atomicNumber ?number. OPTIONAL { ?element table:color ?color. } } 79

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

31 Create your own queries...

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

Create Rules ensure your ontology imports these namespaces: – – SWRL rules are instances of swrl:Imp and can be created by: –Select swrl:Imp, edit body and head. e.g., to formalize the rule that says... (?a hasChild ?c) for swrl:body Parent (?a) for swrl: head

35 Rules Exercise Import jena.owl

36 Configure Inferencing

37 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

38 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

39 Ontology Engineering

40 Ontology Engineering

41

42 Engineering Lifecycle From help system TobBraid Composer tutorial

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

44 Slides acknowledgments Robert Laurini INSA –Lyon TopBraid tutorial