1. Semantic Web for Earth and Environmental Terminology (SWEET) Rob Raskin NASA/JPL PODAAC

2. Purpose SWEET is the largest ontology of Earth system science concepts SWEET is the largest ontology of Earth system science concepts High-level ontology High-level ontology Special emphasis on improving search for NASA Earth system science data resources Special emphasis on improving search for NASA Earth system science data resources Populated manually initially from: Populated manually initially from: GCMD controlled and uncontrolled keywords GCMD controlled and uncontrolled keywords CF terms CF terms Decomposed into facets Decomposed into facets OWL DL for interoperability OWL DL for interoperability Prototype funded by the NASA Earth Science Technology Office

3. Non-Living Substances Living Substances Physical Processes Earth Realm Physical Properties Time Natural Phenomena Human Activities Integrative Ontologies Space Data SWEET Ontologies and Their Interrelationships Faceted Ontologies Units Numerics

4. SWEET Science Ontologies Earth Realms Earth Realms Atmosphere, SolidEarth, Ocean, LandSurface, … Atmosphere, SolidEarth, Ocean, LandSurface, … Properties Properties temperature, composition, area, albedo, … temperature, composition, area, albedo, … Substances Substances CO2, water, lava, salt, hydrogen, pollutants, … CO2, water, lava, salt, hydrogen, pollutants, … Living Substances Living Substances Humans, fish, … Humans, fish, … Processes Processes Diffusion, absorption, … Diffusion, absorption, …

5. SWEET Conceptual Ontologies Phenomena Phenomena ElNino, Volcano, Thunderstorm, Deforestation) ElNino, Volcano, Thunderstorm, Deforestation) Each has associated EarthRealms, PhysicalProperties, spatial/temporal extent, etc. Each has associated EarthRealms, PhysicalProperties, spatial/temporal extent, etc. Specific instances included Specific instances included e.g., 1997-98 ElNino e.g., 1997-98 ElNino Human Activities Human Activities Fisheries, IndustrialProcessing, Economics, Public Good Fisheries, IndustrialProcessing, Economics, Public Good History History State of planet or equipment State of planet or equipment

6. SWEET Numerical Ontologies Numerics Numerics Extents: interval, point, 0, positiveIntegers, … Extents: interval, point, 0, positiveIntegers, … Relations: lessThan, greaterThan, … Relations: lessThan, greaterThan, … SpatialEntities SpatialEntities Extents: country, Antarctica, equator, inlet, … Extents: country, Antarctica, equator, inlet, … Relations: above, northOf, … Relations: above, northOf, … TemporalEntities TemporalEntities Extents: duration, century, season, … Extents: duration, century, season, … Relations: after, before, … Relations: after, before, … Spectral band Spectral band Extents: UV, red, … Extents: UV, red, … Relations: more energetic, … Relations: more energetic, …

7. Data Ontology Dataset characteristics Dataset characteristics Format, data model, dimensions, … Format, data model, dimensions, … Special values Special values Missing, land, sea, ice,... Missing, land, sea, ice,... Parameters Parameters Scale factors, offsets, … Scale factors, offsets, … Data services Data services Subsetting, reprojection, … Subsetting, reprojection, … Quality measures Quality measures

8. Example Reference to SWEET

9. Ontology Design Criteria 1. Manageable: Yield to the broader definition in more general ontology, if available. Keep ontologies small. 2. Scalable: Design must be capable of handling very large vocabularies 3. Orthogonal: Compound concepts should be decomposed into their component parts, to make it easy to recombine concepts in new ways. 4. Extendable: Easily extendable to enable specialized domains to build upon more general ontologies already generated. 5. Application-independence: Structure and contents should be based upon the inherent knowledge of the discipline, rather than on how the domain knowledge is used. 6. Natural language-independence: Structure should provide a representation of concepts, rather than of terms. Synonymous terms (e.g., marine, ocean, sea, oceanography, ocean science) can be indicated as such. 7. Abstraction: Keep objects as classes - only an instance if you can hold them in your hand 8. Community involvement: Community input should guide the development of any ontology.

10. Contact SWEET http://sweet.jpl.nasa.gov SWEET http://sweet.jpl.nasa.govhttp://sweet.jpl.nasa.gov Rob Raskin raskin@seastar.jpl.nasa.gov Rob Raskin raskin@seastar.jpl.nasa.govraskin@seastar.jpl.nasa.gov