Development of a Community Ontology for Earth System Science

1. Development of a Community Ontology for Earth System Science Rob Raskin NASA/Jet Propulsion Laboratory Pasadena, CA March 20, 2008

2. Data to Knowledge Data Information Knowledge Basic Elements Bytes Numbers Models Facts Services Save Visualize Infer Understand Predict Storage File Database GIS Ontology Mind Volume High Low Density Low High Syntax Semantics

3. What is Knowledge? • Facts, relations, meanings, contexts, common sense • Information with context • Shared understanding of meaning • Suitable for reasoning/inference • Dynamic, expandable

4. Application:Intelligent Search for Data • Consults knowledge base to find alternative meanings • Clustered by: synonyms, parent, children • Enables discovery of resources without exact keyword match • Semantic understanding is crucial • Common search engines (Google) use these capabilities only minimally, at present

5. Application: Intelligent Search for Data (cont.) • Noesis ontology-aided search tool • http://noesis.itsc.uah.edu • Provides access to: • Data • Journal articles • Web pages • Experts (people)

6. Ontology • Method to store “facts” • 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 • Support knowledge reuse • Support machine-to-machine communications with deeper semantics than controlled vocabulary

7. Desirable Features of OWL • OWL accepted as a standard by W3C • As a standard language, it is easy to extend (specialize) concepts developed by others • Synonym support (multiple terms with same meaning) • Label available to indicate preferred term for each community • Homonym support (multiple meanings of same term) • Separate namespaces (President:Bush vs Plant:Bush)

8. Plate Tectonics Ontology Plate tectonics - before

9. Atmosphere Ontology Atmosphere Ontology…

10. Semantic Web for Earth and Environmental Terminology (SWEET) • Concept space written in OWL • Initial focus to assist search for data resources • Funded by NASA • Later focus to serve as community standard • Enables scalableclassification of Earth system science concepts

11. SWEET 1.0 Ontologies Faceted Ontologies Living Substances Non-Living Substances Integrative Ontologies Natural Phenomena Physical Processes Human Activities Earth Realm Data Physical Properties Space Time Units Numerics

12. Basic Science/ Math Supporting Geophysical Phenomena Planetary Realms Applications SWEET 2.0 Ontologies: Modular Design Space Time Mathematics Units Mechanics Electric/ Magnetism Thermo Chemistry Geophys Fluid Dynam Radiation Transfer Geo- magnetism Planetary Gravity Planetary Structures Biogeo- chemistry Waves Ocean Troposphere Geosphere Upper Atmosphere Land Surface Heliosphere Ecosphere Cryosphere Human Activities Air Pollution Water Resources Climate Change import Biogeochem Cycles Energy etc.

13. SWEET Numerical Ontologies • Intervals, numeric relations (<,>) • Cartesian products • Functions, derivatives • Fuzzy concepts • “near” • Spatial concepts • 0-D, 1-D, 2-D, and 3-D objects • Coordinate systems • Above, inside, etc. • Temporal concepts • Instant, durations, geological time scales

14. SWEET Data Ontology • Dataset characteristics • Format, data model, dimensions, … • Provenance • Source, processing history, … • Parameters • Scale factors, offsets, … • Data services • Subsetting, reprojection, … • Quality measures • Special values • Missing, land, sea, ice, ...

15. Expressing More Complex Relations in OWL • Many relations are quadruples, not triples • (Temperature hasValue 30 C) • (JohnSmith hasExpertise Geology Expert) • Nested Solution • (Temperature hasValue (30 C)) • (JohnSmith (hasGeology Expertise) Expert)

16. 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 • Gain community buy-in • Involve respected leaders

17. PlanetOnt.org

18. SWEET Future Community Plans • Gain further support from Earth system science community • Workshop at Summer ’08 Meeting of eSIP Federation • Submit SWEET as community standard to NASA Earth Science Standards and Processes Working Group

19. Semantic Web Roadmap Results  Increased Collaboration & Interdisciplinary Science  Improved Information Sharing  Acceleration of Knowledge Production  Revolutionizing how science is done Outcome  Autonomous inference of science results  Geospatial semantic services established  Geospatial semantic services proliferate  Scientific semantic assisted services Output Capability  Semantic geospatial search & inference, access  Common vocabulary based product search and access  Semantic agent-based integration  Semantic agent-based searches Assisted Discovery & Mediation  Basic data tailoring services (data as service), verification/ validation • Interoperable geospatial services(analysis as service), explanation  Metadata-driven data fusion (semantic service chaining), trust  Local processing + data exchange Interoperable Information Infrastructure Technology  SWEET 3.0 with semantic callable interfaces via standard programming languages  SWEET core 2.0 based on best practices decided from community  Reasoners able to utilize SWEET 4.0  SWEET core 1.0 based on GCMD/CF Vocabulary  Geospatial reasoning, OWL-Time  Numerical reasoning  Scientific reasoning Languages/ Reasoning  RDF, OWL, OWL-S Current Near Term Mid Term Long Term

20. Resources • SWEET • http://sweet.jpl.nasa.gov • Ontology development/sharing site • http://PlanetOnt.org • Noesis (search tool) • http://noesis.itsc.uah.edu • SESDI • http://sesdi.hao.ucar.edu