1. M.Benno Blumenthal and John del Corral International Research Institute for Climate and Society OpenDAP 2007 http://iridl.ldeo.columbia.edu/ontologies/ Using Resource Description Framework (RDF) to carry metadata for datasets

2. RDF is important for OpenDAP because By embedding OpenDAP in an RDF document, metadata (a.k.a. attributes) not understood by OpenDAP code are easily carried in a semantically-valid way Explicit relationships between OpenDAP variables can cleanly solve netcdf common name vs OpenDAP GRID/MAP structures, while avoiding retransmission of common independent variables Explicit mapping between the different data models of the different OpenDAP APIs

3. RDF is important for OpenDAP because Support for different languages can be built on top of RDF object support, e.g. Ruby ActiveRDF

4. 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

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

6. Many Data Communities Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema

7. Super Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Standard metadata schema

8. Super Schema: direct Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Standard metadata schema/data service

9. 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

10. RDF Standard Data Model Exchange Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Tools Users Datasets Standard Metadata Schema Standard metadata schema RDF

11. Standard metadata schema Tools Users Datasets Standard Metadata Schema RDF Tools Users Datasets Standard Metadata Schema RDF Tools Users Datasets Standard Metadata Schem RDF RDF Data Model Exchange RDF Tools Users Datasets Standard Metadata Schema RDF Tools Users Datasets Standard Metadata Schema RDF

12. RDF Architecture RDF Virtual (derived) RDF queries

13. 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 have common concepts beyond the least-common- denominator EASIER – tools to enhance the mapping process, mappings build on other mappings

14. CF attributes SWEET Ontologies Search Terms CF Standard Names IRIDL Terms NC basic attributes IRIDL attributes SWEET as Terms CF Standard Names As Terms Gazetteer Terms

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. 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 RDF: framework for writing connections

19. 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”

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

21. WOA01 diagram

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

23. {SST} rdf:type {cfatt:non_coordinate_variable}, {SST} cfatt:standard_name {cf:sea_surface_temperature}, {SST} netcdf:hasDimension {longitude} 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

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

25. Search Interface Term http://iri.columbia.edu/~benno/sampleterm. pdfhttp://iri.columbia.edu/~benno/sampleterm. pdf

26. 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

27. 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

28. Faceted Search Explicated

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

30. Search Interface Semantic API {item} dc:title dc:description rss:link iridl:icon dcterm:isPartOf {item2} dcterm:isReplacedBy {item2} {item} trm:isDescribedBy {term} {term} a {facet} of {taxa} of {trm:Term}, {facet} a {trm:Facet}, {taxa} a {trm:Taxa}, {term} trm:directlyImplies {term2}

31. Faceted Search w/Queries http://iridl.ldeo.columbia.edu/ontologies/query2.pl?...

32. RDF Architecture RDF Virtual (derived) RDF queries

33. Data Servers Ontologies MMI JPL Standards Organizations Start Point RDF Crawler RDFS Semantics Owl Semantics SWRL Rules SeRQL CONSTRUCT Search Queries Location Canonicalizer Time Canonicalizer Sesame Search Interface bibliography IRI RDF Architecture

34. CF attributes SWEET Ontologies Search Terms CF Standard Names IRIDL Terms NC basic attributes IRIDL attributes SWEET as Terms CF Standard Names As Terms Gazetteer Terms

35. RDF is important for OpenDAP because By embedding OpenDAP in an RDF document, metadata (a.k.a. attributes) not understood by OpenDAP code are easily carried in a semantically-valid way Explicit relationships between OpenDAP variables can cleanly solve netcdf common name vs OpenDAP GRID/MAP structures, while avoiding retransmission of common independent variables Explicit mapping between the different data models of the different OpenDAP APIs Build on language support of RDF objects

36. Embedded OpenDAP Ontology

37. Topics/Issues OpenDAP and RDF: can we transport data semantics without fixing the entire schema?OpenDAP and RDF netcdf/HDF and RDF: do we need non- contextual modeling in our metadata transport/storage? Concepts as classes vs concepts as individuals Sub-classes vs sub-categories