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Using RDF/OWL Technologies for Discovery and Use Metadata

Using RDF/OWL Technologies for Discovery and Use Metadata. M.Benno Blumenthal, Michael Bell, John del Corral, and Emily Grover-Kopec International Research Institute for Climate and Society Columbia University http://iridl.ldeo.columbia.edu/. Definitions. Resource Description Framework (RDF)

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Using RDF/OWL Technologies for Discovery and Use Metadata

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  1. Using RDF/OWL Technologies for Discovery and Use Metadata M.Benno Blumenthal, Michael Bell, John del Corral, and Emily Grover-KopecInternational Research Institute for Climate and SocietyColumbia Universityhttp://iridl.ldeo.columbia.edu/

  2. Definitions • Resource Description Framework (RDF) • Web Ontology Language (OWL)

  3. Why RDF? Web-based system for interoperating semantics A key part of the Semantic Web RDF/OWL is an interesting technology, but it is even more interesting when it is clear that it can help solve our problems

  4. The Data Problem Datasets Users

  5. The Tool Interface Datasets Tools Users

  6. Standard Metadata Standard Metadata Schema/Data Services Datasets Tools Users

  7. StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema Datasets Datasets Datasets Datasets Datasets Tools Tools Tools Tools Tools Users Users Users Users Users Many Data Communities

  8. StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema Datasets Datasets Datasets Datasets Datasets Tools Tools Tools Tools Tools Users Users Users Users Users Super Schema Standard metadata schema

  9. StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema Datasets Datasets Datasets Datasets Datasets Tools Tools Tools Tools Tools Users Users Users Users Users Super Schema: direct Standard metadata schema/data service

  10. Flaws • A lot of work • Super Schema/Service is the Lowest-Common-Denominator • Science keeps evolving, so that standards either fall behind or constantly change

  11. StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema Datasets Datasets Datasets Datasets Datasets Tools Tools Tools Tools Tools Users Users Users Users Users RDF Standard Data Model Exchange Standard metadata schema RDF RDF RDF RDF RDF RDF

  12. RDF RDF RDF RDF RDF StandardMetadataSchema StandardMetadataSchema StandardMetadataSchema StandardMetadataSchem StandardMetadataSchema RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF Datasets Datasets Datasets Datasets Datasets Tools Tools Tools Tools Tools Users Users Users Users Users RDF Data Model Exchange Standard metadata schema RDF

  13. queries queries queries RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF RDF Architecture Virtual (derived) RDF

  14. Why is this better? • Maps the original dataset metadata into a standard format that can be transported and manipulated • Still the same impedance mismatch when mapped to the least-common-denominator standard metadata, but • When a better standard comes along, the original complete-but-nonstandard metadata is already there to be remapped, and “late semantic binding” means everyone can use the new semantic mapping • Can uses enhanced mappings between models that are close • EASIER – these are tools to enhance the mapping process

  15. Sample Tool: Faceted Search http://iridl.ldeo.columbia.edu/ontologies/query2.pl?...

  16. Distinctive Features of the search • Search terms are interrelated • terms that describe the set of returns are displayed (spanning and not) • Returned items also have structure (sub-items and superseded items are not shown)

  17. Architectural Features of the search • Multiple search structures possible • Multiple languages possible • Search structure is kept in the database, not in the code http://iridl.ldeo.columbia.edu/ontologies/query2.pl

  18. Cast of RDF Characters

  19. RDF: framework for writing connections Triplets of • Subject • Property (or Predicate) • Object URI’s identify things, i.e. most of the above Namespaces are used as a convenient shorthand for the URI’s

  20. Datatype Properties {WOA} dc:title “NOAA NODC WOA01” {WOA} dc:description “NOAA NODC WOA01: World Ocean Atlas 2001, an atlas of objectively analyzed fields of major ocean parameters at monthly, seasonal, and annual time scales. Resolution: 1x1; Longitude: global; Latitude: global; Depth: [0 m,5500 m]; Time: [Jan,Dec]; monthly”

  21. Object Properties {WOA} iridl:isContainerOf {Grid-1x1}, {Grid-1x1} iridl:isContainerOf {Monthly}

  22. WOA01 diagram

  23. Standard Properties {WOA} dcterm:hasPart {Grid-1x1}, {Grid-1x1} dcterm:hasPart {MONTHLY} Alternatively {WOA} iridl:isContainerOf {Grid-1x1}, {iridl:isContainerOf} rdfs:subPropertyOf {dcterm:hasPart}

  24. netcdf/CF in RDF Object properties provide a framework for explicitly writing down relationships between data objects/components, e.g. vague meaning of nesting is made explicit Properties also can be related, since they are objects too {SST} rdf:type {cfatt:non_coordinate_variable}, {SST} cfatt:standard_name {cf:sea_surface_temperature}, {SST} netcdf:hasDimension {longitude}

  25. Noncontextual Modeling • “noncontextual modeling make RDF the perfect glue between systems and fixed data models” – The Semantic Web

  26. RDF Level • Transport/Exchange (RDF/XML) • Storage • RDF APIs (Redland,Jena,Sesame) • Query (SPARQL,SeRQL, …) • Basic Semantics

  27. RDF SemanticsRDF Primer

  28. RDF-Schema (RDFS)

  29. Gazetteer Classes

  30. Gazetteer Individuals

  31. Search Interface Term • http://iri.columbia.edu/~benno/sampleterm.pdf

  32. Semantics lead to Virtual Triples Transitive: {a} rdfs:subClassOf {b} rdfs:subClassOf {c} implies {a} rdfs:subClassOf {c} i.e. semantics of rdfs:subClassOf imply additional triples not explicitly stated Likewise: {a} rdfs:subPropertyOf{b} rdfs:subPropertyOf {c} implies {a} rdfs:subPropertyOf {c} More interestingly, {a} myprop {b}, {myprop} rdfs:subPropertyOf {prop2} implies {a} prop2 {b}

  33. Subcategories are not subClasses So carelessly translating existing conceptual organizations can get one into trouble

  34. Domain and Range are inherited Since the domain and range of a property are classes, then subclasses “inherit” properties (in this sense)

  35. UML/RDFS • Unified Modeling Language • Base concepts are the same (RDFS lacks methods), so one can export the underlying structure of the code as the underlying structure for the metadata • See Representing UML in RDF

  36. Ontologies Use Conventions to connect concepts to established sets of concepts Generate additional “virtual” triples from the original set and semantics RDFS – some property/class semantics OWL – additional property/class semantics: more sophisticated (ontological) relationships

  37. OWL Language for expressing ontologies, i.e. the semantics are very important. However, even without a reasoner to generate the implied RDF statements, OWL classes and properties represent a sophistication of the RDF Schema However, there is a serious split in world view from what we have been talking about: concepts as classes vs concepts as individuals

  38. OWL

  39. Protégé Tool for editing/displaying Ontologies Different “tabs” display different perspectives http://protege.stanford.edu/

  40. Cast of RDF Characters II

  41. Query Language: SPARQL • (quick reference at http://www.dajobe.org/2005/04-sparql/) • Supported by Redland, Jena, Sesame-2.0 (alpha) • Jena implementation supports url source of triples, i.e. do not even need a triple store • The standard

  42. Query Language: SeRQL • Older than SPARQL • Implemented on top of Sesame • Currently more powerful than SPARQL, i.e. has nested queries

  43. SeRQL DetailsCopied from on-line tutorial • Syntax • Select • Construct • Where • From

  44. SeRQL: basic syntax {person} foo:worksFor {Company} rdf:type {foo:ITCompany}

  45. SeRQL: multiple statements {subj1} pred1 {obj1}; pred2 {obj2} Or {subj1} pred1 {obj1} , {subj1} pred2 {obj2}

  46. SeRQL: short cuts {subj1} pred1 {obj1,obj2,obj3} (also implies obj1,obj2,obj3 are distinct)

  47. SeRQL: Select SELECT dataset, dlabel FROM {dataset} rdf:type {iridl:dataset}, [{dataset} rdfs:label {dlabel}] USING NAMESPACE iridl = <http://iridl.ldeo.columbia.edu/ontologies/iridl.owl> Output as table (XML)

  48. SeRQL:Construct Output as RDF (RDF/XML) CONSTRUCT {dataset} rdf:type {foo:LabelledDatasets} FROM {dataset} rdf:type {iridl:dataset}; rdfs:label {dlabel} USING NAMESPACE iridl = <http://iridl.ldeo.columbia.edu/ontologies/iridl.owl>

  49. Faceted Search Explicated

  50. Search Interface • Items (datasets/maps) • Terms • Facets • Taxa

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