1. SWEET: Upper-Level Ontologies for Earth System Science OPeNDAP Meeting Feb 2007 Rob Raskin PO.DAAC Jet Propulsion Laboratory

2. Data to Knowledge Data InformationKnowledge Basic ElementsBytes NumbersModelsFacts ServicesIngest Archive Visualize Infer Understand Predict StorageFile Database HDF-EOS GIS/MIS Ontology Mind InteroperabilitySyntactic OPeNDAP WMS/WCSSemantic Volume/DensityHigh/LowLow/High StatisticsChecksum Moments DescriptiveInferential Analysis Fourier Wavelet EOF SSA Methodology Exploratory-analysis Model-based-mining SyntaxSemantics

3. Semantics: Shared Understanding of Concepts Provides a namespace for scientific terms…plus Provides descriptions of how terms relate to one another Example tags in markup language: subclass, subproperty, part of, same as, transitive property, cardinality, etc. Enables object in “data space” to be associated formally with object in “science concept space” “Shared understanding” enables software tools to find “meaning” in resources

4. Ontology Representation W3C has adopted four XML-based standard ontology languages: RDF, OWL-Lite, OWL-DL, OWL Full Basic building blocks: Class, subclass, property, subproperty, sameAs Standard language enables anyone to extend an ontology Knowledge built up incrementally

5. Why an Upper-Level Ontology for Earth System Science? Many common concepts used across Earth Science disciplines (such as properties of the Earth) Provides common definitions for terms used in multiple disciplines or communities Provides common language in support of community and multidisciplinary activities Reduced burden (and barrier to entry) on creators of specialized domain ontologies Only need to create ontologies for incremental knowledge

6. Semantic Web for Earth & Environmental Terminology (SWEET) Ontology of Earth system science and data concepts Provides a common semantic framework (or namespace) for describing Earth science information and knowledge Emphasis on improving search for NASA Earth science data resources Represented in OWL-DL

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

8. SWEET Supports Knowledge Reuse SWEET is a concept space Enables scalable classification of Earth science and data- related concepts Enables object in data space to be mapped to science concept space Concept space is translatable into other languages/cultures using “sameAs” notions

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

10. SWEET Conceptual Ontologies Phenomena ElNino, Volcano, Thunderstorm, Deforestation, Terrorism, physical processes (e.g., convection) Each has associated EarthRealms, PhysicalProperties, spatial/temporal extent, etc. Specific instances included e.g., 1997-98 ElNino Human Activities Fisheries, IndustrialProcessing, Economics,…

11. SWEET Numerical Ontologies SpatialEntities Extents: country, Antarctica, equator, inlet, … Relations: above, northOf, … TemporalEntities Extents: duration, century, season, … Relations: after, before, … Numerics Extents: interval, point, 0, positiveIntegers, … Relations: lessThan, greaterThan, … Units Extracted from Unidata’s UDUnits Added SI prefixes Multiplication of two quantities carries units

12. Numerical Ontologies Numeric concepts defined in OWL only through standard XML XSD spec Intervals defined as restrictions on real line Added in SWEET Numerical relations (lessThan, max, …) Cartesian product (multidimensional spaces) Numeric ontologies used to define spatial and temporal concepts

13. XSD: Datatypes Numeric boolean, decimal, float, double, integer, nonNegativeInteger, positiveInteger, nonPositiveInteger, negativeInteger, long, int, short, unsignedLong, unsignedInt, unsignedShort, unsignedByte, hexBinary, base64Binary String String, normalizedString, anyURI, token, language, NMTOKEN, Name, NCName Date dateTime, time, date, gYearMonth, gYear, gMonthDay, gDayxsd:gMonth

14. Data and Services Ontology Formats Data models Data Sttructures Special values Missing, land, sea, ice, etc. Parameters Scale factors, offsets, algorithms Data Services Subset, reproject

15. Example: AIRS Level 2 Dataset Subset of Dataset where DataModel= Level 2 Instrument= AIRS HorizontalDimension= 2 VerticalDimension= 1 Format= HDF-EOS Property= Temperature Substance= Air

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

17. How SWEET was Initially Populated Initial sources GCMD Over 10,000 datasets Over 1000 keywords Data providers submit additional terms for “free-text” search CF Over 700 keywords Very long term names surface_downwelling_photon_spherical_irradiance_in_sea_water Decomposed into facets Property= spherical_irradiance Substance= sea_water Space= surface Direction= down

18. Collaboration Web Site Discussion tools Blog, wiki, moderated discussion board Version Control/ Configuration Management Trace dependencies on external ontologies Tools to search for existing concepts in registered ontologies Ontology Validation Procedure W3C note is formal submission method Registry/discovery of ontologies Support workflows/services for ontology development

19. Community Issues Content Maintain alignment given expansion of classes and properties Standards and Conventions Agreement on standards for use of OWL Fuzzy representation conventions Submit as standard to NASA Standards & Processes Working Group Review Board Who will oversee and maintain for perpetuity (or at least through the next funding cycle)? ESIP Federation? A new consortium? Global Support Provide tools to visualize and appreciate the big picture

20. Update/Matching Issues No removal of terms except for spelling or factual errors Subscription service to notify affected ontologies when changes made Must avoid contradictions Additions can create redundancy if sameAs not used Humans must oversee “matching” CF has established moderator to carry out analogous additions OWL “import” imports entire file Associate community with ontology terms Community tagging

21. Best Practices Keep ontologies small, modular Be careful that “Owl:Import” imports everything Use higher level ontologies where possible Identify hierarchy of concept spaces Model schemas Try to keep dependencies unidirectional

22. Web Sites http://sweet.jpl.nasa.gov http://PlanetOnt.org