1. IRI Data Library Faceted Search: an example of
RDF-based faceted search for climate data
Drawing on multiple ontologies to build an application
Using inference to connect ontologies describing different parts of the framework

2. Faceted Search http://iridl.ldeo.columbia.edu/ontologies/query2.pl?...
Again as an example, here is a user interface built on that ontological structure

3. 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Returned items also have structure (sub-items and superseded items are not shown)

4. Architectural Features of the search
Interface is generated from a set of Terms connected to a set of Items
Multiple search structures possible
Multiple languages possible
Search structure is kept in the database, not in the code

5. Search Interface as Multiple Ontologies
Additional Semantics
Dataset Ontology
Search Ontology
Datasets
Search Interface
Users

6. Ontology Types Attribute Ontology (e.g. Dataset)
Object Ontology (essential for crosswalk)
Term Ontology (e.g. search ontology)

7. Attribute Ontology Subjects are the only type-object
Predicates are “attributes”
Objects are datatype
Isomorphic to simple data tables
Isomorphic to netcdf attributes of datasets
Some faceted browsers: predicate = facet

8. Object Ontology Objects are object-type Isomorphic to “belongs to”
Isomorphic to multiple data tables connected by keys
Express the concept behind netcdf attributes which name variables
Concepts as objects can be cross-walked
Concepts as object can be interrelated

9. Example: controlled vocabulary
{variable} cfatt:standard_name {“string”}
Where string has to belong to a list of possibilities.
{variable} cfobj:standard_name {stdnam}
Where stdnam is an individual of the class cfobj:StandardName

10. Example: controlled vocabulary
Bi-direction crosswalk between the two is somewhat trivial, which means all my objects will have both
cfatt:standard_name
and
cfobj:standard_name

11. Example: controlled vocabulary
If I am writing software to read/write netcdf files, I use the cfatt ontology and in particular cfatt:standard_name
If I am making connections/cross-walks to other variable naming standards, I use
cfobj:standard_name

12. Term Ontology Concepts as individuals
Simple Knowledge Organization System (SKOS) is a prime example
The ontology used here is slightly different than SKOS: facets are classes of terms rather than being top_concepts

13. Nuanced tagging
Concepts as objects can be interrelated: specific terms imply broader terms
Object ends up being tagging with terms ranging from general to specific.
Search can then be nuanced
tagging can proceed in absence of perfect information

14. Faceted Search Explicated
Now let’s revisit the search interface, looking at the semantics and architecture behind it.

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

16. 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}

17. Faceted Search w/Queries

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

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

20. Cast of Characters NC – netcdf data file format
CF – Climate and Forecast metadata convention for netcdf
SWEET - Semantic Web for Earth and Environmental Terminology (OWL Ontology)
IRIDL – IRI Data Library

21. CF attributes
NC basic attributes
IRIDL
attributes/objects
CF data objects
CF Standard Names
(RDF object)
SWEET Ontologies
(OWL)
Location
CF Standard Names
As Terms
IRIDL Terms
SWEET as Terms
Search Terms
Gazetteer Terms

22. See Also http://iridl.ldeo.columbia.edu/ontologies/