Semantic Web for Earth and Environmental Terminology (SWEET) Rob Raskin NASA/JPL July 20, 2006

1. Semantic Web for Earth and Environmental Terminology(SWEET)Rob RaskinNASA/JPLJuly 20, 2006

2. Outline • Why use ontologies? • SWEET ontologies • Update/community processes

3. Why Use Ontologies?

4. Semantic Understanding is Difficult! Sea surface temperature: measured 3 m above surface Sea surface temperature: measured at surface Variable t: temperature Variable t: time Data quality= 5 Let’s eat, Grandma. Let’s eat Grandma. Time flies like an arrow. Fruit flies like a pie. LA Times headline Major combat operations in Iraq have ended

5. Ontologies • General definition: “all that is known” • Computer science definition: Machine-readable definition of terms and how they relate to one another • As with a dictionary, terms are defined in terms of other terms • Provide shared understanding of concepts • Enable deeper semantics than typical controlled vocabulary for machine-to-machine communications

6. Taxonomy vs. Ontology • Taxonomy (librarian perspective) • Subject Classification • Children are subcategory, not necessarily subclass of parent concepts • Example: • EarthScience>Meteorology>WeatherPersonalities>DaveJones • Used by: Library of Congress, Dewey Decimal System, Web OpenDirectory, GCMD Keyword • Ontology (knowledge engineer perspective) • Children are subclasses of parent concepts • Parent properties inherited by children • Multiple inheritance generally supported • Scalable • “New” concepts are often definable using multiple inheritance (e.g. Sea floor temperature) rather than creating a new definition

7. XML-based Ontology Languages • XML satisfies desired properties for language syntax • However, there are too many possible ways that XML tags can be named and used • No standardization of XML tag meanings as in HTML (<b> </b> pair => renders in bold) • Additional standardized semantics needed to exploit shared understanding of concepts • W3C has adopted specializations of XML that predefine particular tags • Resource Description Formulation (RDF) • Ontology Web Language (OWL)

8. Semantic Web Vision • Web page creators place XML tags around technical terms on web pages • XML tags point to ontology where term is defined • Search tools use this information to provide value-added services • Common search engines (Google) use these capabilities only minimally, at present

9. Applications • Software tools can find “meaning” in resources for • Discovery • Fusion • Lineage • … • Requirements • Data products associated with objects in “science concept space” • Richer descriptions than DIFs • Data services associated with objects in “service concept space” • Richer descriptions than SERFs • Search/fusion tools that exploit ontologies

10. SWEET Ontologies

11. SWEET • Comprehensive upper-level ontology of Earth system science concepts • Initial emphasis on improving search for NASA Earth science data resources • Provides common semantic framework for representing Earth science data, information and knowledge • Populated manually initially from: • GCMD controlled and uncontrolled keywords • CF terms Funding provided by the NASA Earth Science Technology Office

12. SWEET Ontologies Integrative Earth Realm Natural Phenomena Physical Processes Physical Properties Human Activities Substances non-living Data Substances Living Auxiliary Space Time Units Numerics

13. SWEET is a Concept Space • Enables scalable classification of Earth science and associated data concepts • Captures scientific philosophies • Reductionism (in orthogonal, facted ontologies) • Holisism (in integrative, unifying ontologies) • Uses standard language (OWL DL) • Enables domain specialists to expand and specialize the work of others • Enables concepts to be translatable into other languages/cultures using “sameAs” notions • Enables use of reasoners and other standard ontology tools

14. 3DLayer Fragment of SWEET subClassOf PlanetaryLayer partOf primarySubstance =“air” Atmosphere partOf AtmosphereLayer upperBoundary =50 km subClassOf subClassOf sameAs= “Lower Atmosphere” lowerBoundary =15 km Troposphere Stratosphere isUpperBoundaryOf isLowerBoundaryOf Tropopause

15. Science Ontology Classes • Earth Realms • Atmosphere, SolidEarth, Ocean, LandSurface, … • Properties (includes default unit) • temperature, composition, area, albedo, … • Substances • CO2, water, lava, salt, hydrogen, pollutants, … • Living Substances • Humans, fish, … • Processes • Diffusion, absorption, …

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

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

18. Properties • Intervals • hasUpperLimit, hasLowerLimit, hasUnit • Applicable to spectral range and vertically structured layers of the Earth • Spatial relations • northOf, above, insideOf, hasDirection • Other numerical relations • hasCoordinate1, lessThan

19. SWEET is Middleware • The intention is for specialized user communities to extend its content • SWEET provides the common sense knowledge of Earth system science that is common to all disciplines • Domain specialists need to add only the incremental knowledge over and beyond the basic Earth system science knowledge • Community can submit extensions back into SWEET • “sameAs” tags can be tagged with your community name

20. SWEET as an Upper Level Earth Science Ontology Math Physics Chemistry Space import Property EarthRealm Process, Phenomena Substance Data Time SWEET import Stratospheric Chemistry Biogeochemistry Specialized domains

21. Earth Science Ontologies • Numerics are limited • No Cartesian product (multidimensional) space predefined • No numeric relations (+, <, >, …) • Community conventions must standardize extensions to language

22. Update/Community Processes

23. SWEET Users • ESML- Earth Science Markup Language • ESIP - Earth Science Information Partner Federation • GEON- Geosciences Network • GENESIS- Global Environmental & Earth Science Information System • IRI- International Research Institute (Columbia) • LEAD- Linked Environments for Atmospheric Discovery • MMI- Marine Metadata Initiative • NOESIS • PEaCE- Pacific Ecoinformatics and Computational Ecology • SESDI- Semantically Enabled Science Data Integration • VSTO- Virtual Solar-Terrestrial Observatory

24. Community Objectives • Enable domain specialists to use and extend SWEET content • Enable SWEET ontology to be accepted as a community standard • Submit SWEET to the NASA Earth Science Standards Process Group during 2007

25. Collaboration Web Site • Basics • Blog, wiki, moderated discussion board, version control, validation services • Search across ontologies • Trace of dependencies across ontologies • RSS service to notify ontology developers when change has been made • Policy is to remove term only if absolutely necessary, to remain backward compatibility • Expansion into new domains • Geology, upper atmosphere, hydrosphere • Review board

26. For more information… • http://sweet.jpl.nasa.gov